The clinical value of transcranial doppler ultrasonography in patients ...

Annemarie D. Wijnhoud

The clinical value of transcranial Doppler ultrasonography in patients with a recent TIA or non-disabling

ischemic stroke

Annemarie D. Wijnhoud

ISBN: 978-94-6169-322-8

Layout and printing: Optima Grafische Communicatie, Rotterdam, The Netherlands

The Clinical Value of Transcranial Doppler Ultrasonography in Patients with a Recent TIA

or Non-Disabling Ischemic Stroke

De klinische waarde van transcranieel Doppler ultrageluid bij patiënten met een recente TIA

of licht herseninfarct

Proefschrift

ter verkrijging van de graad van doctor aan de

Erasmus Universiteit Rotterdam

op gezag van de rector magnificus

prof.dr. H.G. Schmidt

en volgens besluit van het College voor Promoties.

De openbare verdediging zal plaatsvinden op

Donderdag 22 november 2012

om 09.30 uur

door

Annemarie Dagmar Wijnhoud

geboren te Zwolle

Promotiecommissie

Promotoren: Prof.dr. D.W.J. Dippel

Prof.dr. P.J. Koudstaal

Overige leden: Prof.dr. A. van der Lugt

Prof.dr. E.W. Steyerberg

Prof.dr. J. Stam

contents

1. General introduction 7

2. The diagnostic value of transcranial Doppler ultrasonography in patients with a

recent TIA or ischemic stroke

2.1 Relationships of transcranial blood flow Doppler parameters with major

vascular risk factors: TCD study in patients with a recent TIA or non-

disabling ischemic stroke

17

2.2 Skull thickness and bone density as predictors of an inadequate

acoustical temporal bone window in transcranial Doppler ultrasound

31

2.3 Diagnosis of ischemic stroke subtype and potential cardiac sources of

embolism by transcranial Doppler ultrasonography. A systematic review

45

3. The prognostic value of transcranial Doppler ultrasonography in patients with a

recent TIA or ischemic stroke

3.1 Prediction of major vascular events in patients with a recent TIA or

ischemic stroke. A comparison of 7 models

65

3.2 The prognostic value of pulsatility index, flow velocity, and their ratio,

measured with TCD ultrasound, in patients with a recent TIA or ischemic

stroke.

81

3.3 Micro-embolic signals and risk of recurrent stroke in patients with a TIA or

ischemic stroke

95

3.4 Improving prediction of major vascular events in patients with a TIA or

ischemic stroke with transcranial Doppler ultrasonography

105

4. General discussion 115

Summary 131

Samenvatting 137

List of Abbrevations 143

List of Publications 147

About the Author 151

Dankwoord 155

chapter 1General introduction

General introduction 9

Stroke is the third leading cause of death in developed countries, after heart disease and

cancer, and the first cause of disability.1 Most strokes are ischemic and caused by occlusion of

a cerebral artery. This leads to dysfunction and eventually death of brain tissue through lack of

oxygen. This results in typical symptoms such as unilateral weakness, language disturbances,

unilateral sensory disturbances, hemianopia, ataxia, or impaired speech. In the acute phase of

tissue dysfunction, patients can be treated with thrombolytic agents, but treatment should be

started within 4,5 hours after onset of symptoms. However, at present, only 25% of patients are

eligible for this treatment, and even when patients can be treated, treatment is not always suc-

cessful.2 In many patients, cerebral ischemia is only transient and does not result in persistent

symptoms and disability. These Transient Ischemic Attacks (TIAs) or minor ischemic strokes

offer the opportunity to prevent major, disabling strokes or other vascular events. Secondary

prevention is therefore one of the main objectives of stroke management.

Risk of recurrent stroke is approximately 9-16% annually after ischemic stroke. Intensive

secondary prevention by use of antiplatelet medication and treatment of high blood pressure

and high cholesterol has reduced the annual risk of recurrent events to approximately 4.5%.3

The most well-known risk factors for stroke or other major vascular events such as myocardial

infarction or vascular death are age, male sex, hypertension, diabetes, and smoking. There are

many other risk factors such as white matter lesions, carotid or vertebral artery stenosis, and

atrial fibrillation. Unfortunately, even with this large number of prognostic factors, it is still hard

to discriminate between patients with a high risk of recurrent stroke and patients with a low

risk of recurrent stroke. It has therefore been contended that it is important to identify new risk

factors for the occurrence of stroke and other major vascular events.4

Transcranial Doppler ultrasonography, the main topic of this thesis, offers noninvasive infor-

mation on flow velocity, cerebral CO2 reactivity, and the presence of micro-embolic signals.

These three parameters may provide new predictors of increased risk of stroke recurrence and

other vascular complications. Transcranial Doppler ultrasonography allows the noninvasive

investigation of arterial blood flow within the skull.5 It was first described in 1982 by Aaslid et

al.5 Low frequency (2 MHz) ultrasound can pass through the bone at the level of the temporal

window, which is located just above the ear where the temporal bone is the thinnest. Pulsed

wave ultrasound is reflected by flowing blood, which reflects the ultrasound wave. This causes

a phase shift, wherein the frequency is decreased or increased, depending on which direction

the blood is flowing. This frequency change correlates directly with the blood flow velocity. This

is called the Doppler effect. With this technique several parameters can be studied in the main

cerebral arteries: flow velocities (mean flow velocity, peak flow velocity, and end-diastolic flow

velocity), cerebral CO2 reactivity, and micro-embolic signals (MES), which are described below.

Chap

ter 1

10

Flow velocity parameters

As the velocity in the major cerebral arteries is dependent on the heartbeatcycle, peaksys-

tolic flow velocity (PSV) and end-diastolic flow velocity (EDV) can be defined as parameters

(Figure 1). With these parameters mean flow velocity (MFV) can be calculated:

MFV= EDV + 1/3(PSV-EDV).

Pulsatility index (PI), a measure of peripheral vascular resistance can be calculated as:

(PSV-EDV)/MFV

High flow velocity parameters are diagnostic for a middle cerebral artery (MCA) stenosis. A

mean flow velocity of > 100 cm/s or a PSV of > 140 cm/s is highly suggestive of a MCA stenosis

of more than 50%.6 A MCA stenosis is, however, rare in Caucasian patients.7,8 patients with a

MCA stenosis of more than 50% have an increased risk of recurrent stroke compared to patients

without a MCA stenosis. MFV in the MCA is related to age and sex. MFV decreases with age9

and MFV is higher in women.10 The relationship with other vascular risk factors in unclear. In

healthy elderly patients an increased MFV is related to increased risk of stroke.11 Before TCD

parameters can be studied as diagnostic or prognostic factors, these relationships will have to

be investigated.

cerebral co2-reactivity

The compliance of the cerebral circulation, also called the cerebral vasomotor reactivity or

cerebral CO2-reactivity, can be measured.12 The cerebral CO2-reactivity measures the flow

velocity change in a major cerebral artery during hypercapnia. During hypercapnia distal

vasodilatiation occurs and therefore the flow velocity in the observed major artery will have

to rise. The cerebral CO2-reactivity is the percentage increase in flow velocity in the observed

Figure 1: Example of TCD signal: Flow velocity in the left middle cerebral artery. On the X-axis is the timeline (in seconds), on the y-axis the flow velocity in cm/sec.


major artery, usually the middle cerebral artery (Figure 2). This is thought to reflect the vascular

reserve capacity in the brain.

Cerebral CO2-reactivity diminishes in patients with a severe carotid artery stenosis or occlu-

sion, and is a predictor of recurrent stroke in these patients.13,14 It is unknown whether this

applies for patients without a carotid artery stenosis. An impaired cerebral CO2-reactivity is

related to various vascular risk factors such as hyperlipidemia and diabetes, and to the presence

of white matter lesions on MRI scan of the brain.15-17 In patients with a lacunar infarction, the

cerebral CO2-reactivity is lower than in healthy controls.18 This may suggest that an impaired

cerebral CO2-reactivity is a prognostic factor for stroke. The cerebral CO2-reactivity seems to

distinguish between patients with a cortical infarction and patients with a lacunar infarction,19

but this has not been reproduced. The diagnostic and prognostic value of the cerebral CO2-

reactivity in patients without a carotid artery stenosis is therefore still unknown.

micro-embolic signals

With continuous TCD registration, circulating micro-embolic signals (MES) can be detected

(figure 3). Due to increased scattering and reflection of ultrasound from the embolus, compared

Figure 2: example of Cerebral CO2-reactivity.The x-axis represents the time line. The upper lines represent the flow velocities in the left (red line) and right (green line) middle cerebral arteries measured in cm/s (y-axis). The lower lines represent the end-tidal CO2 (blue line, and the actual expired CO2 concentration (red line). Note that flow velocities increase during hypercapnia and quickly return to normal during normal ventilation. The percentage increase in mean flow velocity during hypercapnia represents the cerebral CO2 reactivity.

Chap

ter 1

12

with the surrounding red blood cells, an embolus appears as a short duration high intensity

signal within the Doppler flow spectrum.

MES occur more frequently in acute stroke patients with a history of TIA or ischemic stroke20

and in patients with symptomatic or asymptomatic carotid stenosis.21-23 In these patients

the presence of MES constitutes a higher stroke risk. Higher prevalence rates are reported in

patients with atrial fibrillation compared to those without. Patients with a mechanical heart

valve have more frequent and louder MESs than those with a biological valve.24-26 These MES

are thougth to be gaseous, not solid.27 All together MES may be of importance in detecting

potential sources of cardiac28 (or extracranial) embolism.

Furthermore, the presence of MES may play a role in differentiating between stroke sub-

types. In patients with lacunar infarction (small vessel disease) MES were observed less often

than in patients with non-lacunar infarcts,which are often caused by cardiac embolism or large

vessel disease.29

Feasibility of tcD investigation

TCD ultrasound is a noninvasive procedure. It takes approximately 30 minutes. The use of head-

bands and semi-automated MES detection greatly improves its applicability in clinical practise.

In approximately 10 to 20% of the patients, no adequate Doppler signal can be obtained.30 It

has been postulated that the thickness of the temporal window plays a crucial role here.

Aim of this thesis

The overall aim of my thesis is to investigate whether it is worthwile to perform a TCD investiga-

tion for diagnostic and prognostic purposes on all patients with a recent TIA or minor ischemic

stroke.

Figure 3: Example of a TCD signal in the middle cerebral artery with a micro-embolic signal (white arrow)


My research questions are:

1. Can TCD be of diagnostic value in detetecting the presence of a potential cardiac source of

embolism and the presence of small vessel disease in patients with a TIA or minor ischemic

stroke?

2. Is it possible to identify patients with a high risk of recurrent vascular events after TIA or

minor ischemic stroke by means of TCD investigation?

Firstly, we assessed the diagnostic value of TCD in a large cohort of patients with a recent TIA

or non-disabling ischemic stroke (Chapter 2.1). We therefore analysed the relationship of the

above mentioned TCD parameters with vascular risk factors and evaluated the value of TCD in

screening for a potential cardiac cause of embolism (PCSE) and for stroke subtype (Chapter 2.3).

In Chapter 2.2 we describe which patients have a high risk of having window failure.

Secondly, we assessed the prognostic value of TCD in patients with a recent TIA or non-

disabling ischemic stroke. We therefore analysed the prognostic value of the different TCD

parameters for a recurrent major vascular event (Chapter 3.2 and 3.3). We then validated several

prediction models on the data from the present study (Chapter 3.1), and evaluated if these TCD

parameters improved existing predicition models (Chapter 3.4).

Chap

ter 1

14

reFerences

1. Feigin VL, Lawes CM, Bennett DA, Anderson CS. Stroke epidemiology: a review of population-based studies of incidence, prevalence, and case-fatality in the late 20th century. Lancet Neurol 2003;2:43-53.

2. Boode B, Welzen V, Franke C, van OR. Estimating the number of stroke patients eligible for thrombo-lytic treatment if delay could be avoided. Cerebrovasc Dis 2007;23:294-8.

3. Diener HC, Sacco RL, Yusuf S, Cotton D, Ounpuu S, Lawton WA, Palesch Y, Martin RH, Albers GW, Bath P, Bornstein N, Chan BP, Chen ST, Cunha L, Dahlof B, De KJ, Donnan GA, Estol C, Gorelick P, Gu V, Hermansson K, Hilbrich L, Kaste M, Lu C, Machnig T, Pais P, Roberts R, Skvortsova V, Teal P, Toni D, Van-derMaelen C, Voigt T, Weber M, Yoon BW. Effects of aspirin plus extended-release dipyridamole versus clopidogrel and telmisartan on disability and cognitive function after recurrent stroke in patients with ischaemic stroke in the Prevention Regimen for Effectively Avoiding Second Strokes (PRoFESS) trial: a double-blind, active and placebo-controlled study. Lancet Neurol 2008;7:875-84.

4. Dippel DWJ, Koudstaal PJ. We need stronger predictors of major vascular events in patients with a recent transient ischemic attack or nondisabling stroke. Dutch TIA Trial Study Group. Stroke 1997;28:774-6.

5. Aaslid R, Markwalder TM, Nornes H. Noninvasive transcranial Doppler ultrasound recording of flow velocity in basal cerebral arteries. J Neurosurg 1982;57:769-74.

6. Wong KS, Huang YN, Gao S, Lam WW, Chan YL, Kay R. Intracranial stenosis in Chinese patients with acute stroke. Neurology 1998;50:812-3.

7. Felberg RA, Christou I, Demchuk AM, Malkoff M, Alexandrov AV. Screening for intracranial stenosis with transcranial Doppler: the accuracy of mean flow velocity thresholds. J Neuroimaging 2002;12:9-14.

8. Sacco RL, Kargman DE, Gu Q, Zamanillo MC. Race-ethnicity and determinants of intracranial athero-sclerotic cerebral infarction. The Northern Manhattan Stroke Study. Stroke 1995;26:14-20.

9. Grolimund P, Seiler RW. Age dependence of the flow velocity in the basal cerebral arteries--a transcra-nial Doppler ultrasound study. Ultrasound Med Biol 1988;14:191-8.

10. Marinoni M, Ginanneschi A, Inzitari D, Mugnai S, Amaducci L. Sex-related differences in human cere-bral hemodynamics. Acta Neurol Scand 1998;97:324-7.

11. Bos MJ, Koudstaal PJ, Hofman A, Witteman JC, Breteler MM. Transcranial Doppler hemodynamic parameters and risk of stroke: the Rotterdam study. Stroke 2007;38:2453-8.

12. Markus HS, Harrison MJ. Estimation of cerebrovascular reactivity using transcranial Doppler, includ-ing the use of breath-holding as the vasodilatory stimulus. Stroke 1992;23:668-73.

13. Webster MW, Makaroun MS, Steed DL, Smith HA, Johnson DW, Yonas H. Compromised cerebral blood flow reactivity is a predictor of stroke in patients with symptomatic carotid artery occlusive disease. J Vasc Surg 1995;21:338-44.

14. Markus H, Cullinane M. Severely impaired cerebrovascular reactivity predicts stroke and TIA risk in patients with carotid artery stenosis and occlusion. Brain 2001;124:457-67.

15. Bakker SL, de Leeuw FE, Koudstaal PJ, Hofman A, Breteler MM. Cerebral CO2 reactivity, cholesterol, and high-density lipoprotein cholesterol in the elderly. Neurology 2000;54:987-9.


16. Fulesdi B, Limburg M, Bereczki D, Michels RP, Neuwirth G, Legemate D, Valikovics A, Csiba L. Impair-ment of cerebrovascular reactivity in long-term type 1 diabetes. Diabetes 1997;46:1840-5.

17. Bakker SL, de Leeuw FE, de Groot JC, Hofman A, Koudstaal PJ, Breteler MM. Cerebral vasomotor reactivity and cerebral white matter lesions in the elderly. Neurology 1999;52:578-83.

18. Molina C, Sabin JA, Montaner J, Rovira A, Abilleira S, Codina A. Impaired cerebrovascular reactivity as a risk marker for first-ever lacunar infarction: A case-control study. Stroke 1999;30:2296-301.

19. Gur AY, Gucuyener D, Uzuner N, Gilutz Y, Ozdemir G, Korczyn AD, Bornstein NM. Cerebral vasomotor reactivity of patients with acute ischemic stroke: Cortical versus subcortical infarcts: an Israeli-Turkish collaborative study. J Neurol Sci 2007;257:121-5.

20. Tong DC, Albers GW. Transcranial Doppler-detected microemboli in patients with acute stroke. Stroke 1995;26:1588-92.

21. Markus HS, Mackinnon A. Asymptomatic Embolization Detected by Doppler Ultrasound Predicts Stroke Risk in Symptomatic Carotid Artery Stenosis. Stroke 2005;36:971-5.

22. Molloy J, Markus HS. Asymptomatic embolization predicts stroke and TIA risk in patients with carotid artery stenosis. Stroke 1999;30:1440-3.

23. Babikian VL, Hyde C, Pochay V, Winter MR. Clinical correlates of high-intensity transient signals detected on transcranial Doppler sonography in patients with cerebrovascular disease. Stroke 1994;25:1570-3.

24. Tong DC, Bolger A, Albers GW. Incidence of transcranial Doppler-detected cerebral microemboli in patients referred for echocardiography. Stroke 1994;25:2138-41.

25. Markus HS. Microembolic signals in patients referred for echocardiography. Stroke 1995;26:525-6.

26. Georgiadis D, Konig M, Zunker P, Nabavi D, Stogbauer F, Ringelstein EB. Microembolic signals in patients referred for echocardiography. Stroke 1995;26:525-7.

27. Georgiadis D, Baumgartner RW, Karatschai R, Lindner A, Zerkowski HR. Further evidence of gaseous embolic material in patients with artificial heart valves. J Thorac Cardiovasc Surg 1998;115:808-10.

28. Sliwka U, Job FP, Wissuwa D, Diehl RR, Flachskampf FA, Hanrath P, Noth J. Occurrence of transcranial Doppler high-intensity transient signals in patients with potential cardiac sources of embolism. A prospective study. Stroke 1995;26:2067-70.

29. Grosset DG, Georgiadis D, Abdullah I, Bone I, Lees KR. Doppler emboli signals vary according to stroke subtype. Stroke 1994;25:382-4.

30. Marinoni M, Ginanneschi A, Forleo P, Amaducci L. Technical limits in transcranial Doppler recording: inadequate acoustic windows. Ultrasound Med Biol 1997;23:1275-7.

chapter 2.1Relationships of transcranial blood flow Doppler

parameters with major vascular risk factors: TCD study in patients with a recent TIA or non-

disabling ischemic stroke

A.D. Wijnhoud

P.J. Koudstaal

D.W.J. Dippel

J Clin Ultrasound. 2006 Feb;34:70-6

Chap

ter 2

.1

18

AbstrAct

Purpose: The relationship between intracranial vascular disease and cardiovascular risk factors,

such as smoking, hypertension, diabetes mellitus, and total serum cholesterol in patients with

recent cerebral ischemia is not well-established. We used transcranial Doppler ultrasonography

(TCD) tests as parameters of intracranial vascular disease, and investigated the relationship

between these parameters and conventional cardiovascular risk factors.

Methods: We prospectively studied 598 patients with a minor ischemic stroke or TIA. In all

patients, flow velocities in the left and right MCA, as well as the cerebrovascular CO2 reactivity

were measured by means of TCD. Student’s t-test and linear regression analysis were used to

determine the relationship between the baseline characteristics, vascular risk factors and TCD

parameters.

Results: After adjustment for other vascular risk factors, a statistically significant relationship

with mean flow velocity in the MCA was found for age (3.5 cm/s/10 yrs of age, 95% C.I.: 2.5 to 4.5

cm/s/10yrs, p<0.0001), sex (-2.9 cm/s for male sex, 95% C.I.: -5.5 to -0.3 cm/s, p=0.03), diabetes

(5.6 cm/s for diabetics, 95% C.I.: 2.1 to 9.1 cm/s, p=0.002), and total serum cholesterol (2.4 cm/s

per mmol increase in total serum cholesterol, 95% C.I.:1.4 to 3.5 cm/s, p<0.0001). Total serum

cholesterol and hypertension were related to cerebrovascular CO2 reactivity.

Conclusion: Cerebral flow velocity is influenced by multiple interacting factors. Results of TCD

investigations will have to be adjusted for age, sex, diabetes, and cholesterol when they are

used for diagnostic or prognostic purposes.

TCD and vascular risk factors 19

introDuction

The relationship between cardiovascular risk factors and intracranial vascular disease in

patients with a recent TIA or minor stroke is difficult to ascertain. This is at least partly due

to the inaccessibility of particularly small brain vessels, the difficulty to relate, with certainty,

brain infarcts on CT or MRI to intracranial disease, and the invasive nature of some radiological

imaging procedures. We do know, however, that certain established cardiovascular risk factors,

such as hypertension and diabetes mellitus, are related to cerebral white matter lesions1 and

to silent, mostly lacunar, brain infarcts on CT and MRI.2 Of other cardiovascular risk factors like

serum cholesterol level, the relationship with manifestations of intracranial vascular disease still

remains to be elucidated.3

Ultrasonography may play a role in determining the relationship between these cardio-

vascular risk factors and intracranial atherosclerosis, since the major arteries within the brain

can be relatively easily, non-invasively, and dynamically monitored by means of transcranial

Doppler ultrasound (TCD).4 With TCD, flow velocities in the large arteries in the brain can be

easily assessed through the temporal bone window.5 Moreover, the cerebrovascular reactiv-

ity to a vasodilatory stimulus like CO2, can be assessed with TCD.6 This is thought to reflect

the vascular reserve capacity in the brain, and predicts stroke in patients with a severe carotid

artery occlusion.7

Before TCD parameters could be used as valid diagnostic or prognostic factors, their

relationship with conventional cardiovascular risk factors needs to be studied, because these

risk factors are likely to influence either arterial flow velocity in the major cerebral arteries, or

cerebrovascular reserve capacity, or both. Previous studies have shown that the mean flow

velocity in the major arteries in the brain is sex- and age- dependent.8,9 Some studies have also

shown a sex- and age-dependent effect on cerebrovascular reactivity, measured by transcranial

Doppler ultrasono graphy.10

We therefore studied the relationship between established cardiovascular risk factors and

TCD parameters such as mean flow velocity, peak systolic flow velocity, end diastolic flow veloc-

ity, pulsatility index, and cerebrovascular reactivity to CO2, in a large series of patients with a

recent TIA or minor ischemic stroke.

methoDs

subjects

We studied patients from the Rotterdam TCD study, a prospective study that investigates the

diagnostic and prognostic value of TCD in patients with a recent TIA or ischemic non-disabling

stroke. Inclusion criteria were a recent (<6 months) TIA or non-disabling ischemic stroke;

excluded were patients with a mechanical heart valve and patients with a planned carotid

Chap

ter 2

.1

20

endarterectomy. Only patients who were over 18 years of age and gave informed consent were

included in our study.

The study was approved by the institutional review board and medical ethics committee. Oral

and written informed consent was obtained from all participants, and kept on file.

tcD recordings

All patients underwent TCD examination (Multidop X-4, DWL, Sipplingen, Germany). TCD

examination was performed within 6 months after TIA or non-disabling ischemic stroke. In all

patients peak flow velocity (PSV) and enddiastolic flow velocity (EDV) was measured with a

handheld 2 MHz probe in both middle cerebral arteries (MCAs). Mean flow velocity (MFV) was

calculated as EDV + 1/3(PSV-EDV). The pulsatility index (PI) was calculated as (PSV-EDV)/MFV.

After that, the mean flow velocity in the MCA on both sides was measured continuously with

2x2MHz probes, held in position by a metal headband. Patients breathed through a tightly

fitting air mask. Carbon dioxide concentrations in this mask were measured continuously with

a carbon-dioxide analyzer (Multinex, Datascope). End-tidal CO2 pressure was assumed to reflect

arterial CO2.11 Patients first breathed room air through the mask for at least two minutes until

the mean flow velocity in the MCA had stabilized. Patients then breathed 5% carbon dioxide

in oxygen for at least two minutes, until the mean flow velocity in the MCA had stabilized for

at least 30 seconds. The mean flow velocity in both MCA’s was measured during inspiration of

normal air and during inspiration of 5% carbon dioxide in oxygen, both times after stabilization

of the mean MCA flow velocity. TCD-8 software (DWL) to determine the cerebrovascular CO2-

reactivity (CVR) was used. All data were stored on hard disk for off-line analysis. We calculated

the cerebovascular CO2-reactivity as the percentage rise in mean flow velocity during hyper-

capnia.

All TCD recordings were done by one investigator (A.W.). Blood pressure was measured auto-

matically with a self-inflating cuff (Dynamap, Datascope, The Netherlands) before and during

the TCD recordings.

Laboratory investigations

Total cholesterol, LDL-cholesterol, and HDL-cholesterol levels were measured by means of

standard methods, with a Roche/Hitachi 917 (Mannheim, Germany). The cholesterol-HDL ratio

was calculated. Blood samples were taken at least five days after the onset of the TIA or ischemic

stroke.

Ancillary investigations

All patients underwent routine workup including neurological examination, a CT scan to rule

out hemorrhage, and ECG. A duplex-ultrasound scan of the carotid arteries was made in all

patients with an anterior circulation stroke.


risk factors

Hypertension was defined by a regular blood pressure exceeding 140/90 mm Hg during 2 epi-

sodes of continuous blood pressure measurement or use of anti-hypertensive drugs. Diabetes

was defined by fasting serum glucose over 7.9 mmol/l, or non-fasting serum glucose over 11.0

mmol/l, or use of antidiabetic medication. Regular drinking of alcohol entailed an intake of at

least 1 unit per week. Smoking was defined as smoking of at least one cigarette or cigar a day on

average.

statistical analysis

The mean of the right and left flow velocity parameters and the mean of the right and left

CVR were used for the analyses if both MCA’s could be insonated adequately. In patients with

one-sided window-failure, TCD parameters in the contralateral MCA were used. Student’s t-test

and linear regression analysis, two-tailed, was used to determine the relationship between the

baseline characteristics, major risk factors and TCD parameters in order to detect possible con-

founding factors. A p-value smaller than 0.05 was considered to indicate statistical significance.

No adjustments for multiple testing were made. After that, multiple linear regression analysis

was used to adjust the relationship between TCD parameters and each risk factor for the effects

of the other vascular risk factors.

resuLts

We included 598 consecutive patients in our study. In 4 patients the diagnosis was revised shortly

after inclusion (1 patient had Multiple Sclerosis, 2 had partial epilepsy, and 1 had migraine),

which left 594 patients. In 104 of these, we failed to obtain adequate Doppler data due to two-

sided window failure or other limitations. Therefore, 490 patients were included in the present

analysis. Mean age was 60 years, and two thirds of the patients were men. Approximately half of

the patients had had transient symptoms and more than 75% had focal ischemia in the anterior

circulation. Almost one third of the patients were current smokers, nearly half of the patients had

hypertension, and approximately 17% had diabetes mellitus (Table 1). Nearly 25% of the patients

had one-sided window failure. Age in patients with window failure was significantly higher than

in patients without window failure (60 ± 13 vs. 71 ± 10, p<0.001). Window failure was more often

present in female patients than in male patients (31% vs 9%, p<0.001). The distribution of hyper-

tension, diabetes, and serum cholesterol level did not differ significantly between patients with

window failure and patients without window failure. The proportion of patients who were current

smokers was lower in patients with window failure as compared to patients without window

failure (16 vs. 28%, p<0.05).

Chap

ter 2

.1

22

No statistically significant difference was observed between the TCD parameters of the

mean of left and right MCA and between the TCD parameters on the symptomatic and the

asymptomatic side.

Age

All cerebral blood flow velocity measures (MFV, PSV, EDV), but not cerebrovascular CO2-reactiv-

ity declined significantly with increasing age. The pulsatility index increased significantly with

increasing age. After adjustment for other cardiovascular risk factors, these relationships did

not change in size or direction. In women the decline in cerebral flow velocity was higher than

in men: -5.0 cm/s vs. –2.8 cm/s per 10 years of age.

sex

Blood flow velocity was higher in female than in male patients. This sex-related difference

in cerebral flow velocity was present in younger people. After the age of 60 there was no

table 1: Patient characteristics.

Men N=324 Women N=166 All N=490 p

Demographics

Age, years (mean ± SD) 62 ± 12 56 ± 14 60 ± 13 <0.0001

Stroke characteristics

TIA 169 (52%) 94 (56%) 263 (54%) NS

Anterior circulation TIA or stroke 253 (80%) 139 (84%) 392 (82%) NS

Infarct on CT scan (old or recent) 158 (49%) 65 (39%) 223 (46%) 0.046

Lacunar syndrome 116 (36%) 59 (36%) 175 (36%) NS

White matter lesions 47 (14%) 14 (8%) 61 (12%) 0.055

Risk factors

Smoking, present 95 (29%) 43 (26%) 138 (28%) NS

Alcohol consumption 323 (66%)

Hypertension 179 (55%) 78 (47%) 257 (52%) 0.088

Diabetes 48 (15%) 29 (17%) 77 (16%) NS

Previous TIA or stroke 75 (23%) 33 (20%) 108 (22%) NS

Previous myocardial infarction 43 (13%) 10 (6%) 53 (11%) 0.015

Carotid artery stenosis (≥70%) 30 (9%) 7 (4%) 37 (7%) 0.046

Body-mass-index, kg/m2 (mean ± SD) 26.2 ± 3.4 26.1 ± 4.7 26.2 ± 3.9 NS

Use of cholesterol lowering medication 83 (26%) 38 (24%) 121 (25%) NS

Cholesterol

Total cholesterol,mmol/l (mean ± SD) 5.6 ± 1.1 6.0 ± 1.2 5.7 ± 1.2 <0.0001

HDL-cholesterol, mmol/l (mean ± SD) 1.2 ± 0.4 1.5 ± 0.5 1.3 ± 0.4 <0.0001

LDL-cholesterol, mmol/l (mean ± SD) 3.8 ± 1.1 3.8 ± 1.1 3.8 ± 1.1 NS

Cholesterol-HDL ratio (mean ± SD) 5.0 ± 1.7 4.3 ± 1.6 4.7 ± 1.6 <0.0001


difference in MFV, PDV, and EDV between men and women. No difference in cerebrovascular

CO2-reactivity was found between male and female patients.

current smoking

In patients who were still smoking at the time of TCD investigation the MFV and PSV was

higher than in patients who had quit smoking or had never smoked at all. After adjustment for

age, however, the relationship between smoking and the MFV was not statistically significant

anymore.

hypertension

In hypertensive patients the MFV was lower, and the PI was higher than in normotensive

patients unadjusted for other risk factors. These relationships did not remain statistically signifi-

cant after adjustment for age. The cerebrovascular CO2-reactivity reactivity was 3.1% (p<0.03)

lower in patients with hypertension (Table 3), and 4.1% (p=0.01) lower after adjustment for the

remaining vascular risk factors (Table 4).

Diabetes

MFV and PSV were higher in diabetic patients, whereas PI was lower in diabetic patients. After

adjustment for age and other vascular risk factors, these relationships did not change in size

or direction and remained statistically significant. Diabetes was not related to cerebrovascular

CO2-reactivity.

table 2: TCD parameters in a cohort of 490 patients with a TIA or minor stroke.

TCD Parameter Men N=324 Women N=166 All N=490 P

Mean of both sides

Mean flow velocity (cm/s) 49 ± 15 56 ± 13 51 ± 14 <0.0001

Peak systolic flow velocity (cm/s) 81 ± 23 90 ± 20 84 ± 22 <0.0001

Enddiastolic flow velocity (cm/s) 33 ± 12 38 ± 12 35 ± 12 <0.0001

Pulsatility index 0.95 ± 0.22 0.89 ± 0.20 0.93 ± 0.22 0.008

Cerebrovascular CO2-reactivity (% increase in MFV)

33.4 ± 16.2 33.7 ± 15.2 33.5 ± 16.0 NS

Symptomatic side

Mean flow velocity (cm/s) 49 ± 19 57 ± 15 51 ± 18 <0.0001

Peak systolic flow velocity (cm/s) 80 ± 28 92 ± 23 84 ± 27 <0.0001

Enddiastolic flow velocity (cm/s) 33 ± 16 39 ± 13 35 ± 12 <0.0001

Pulsatility index 0.95 ± 0.25 0.89 ± 0.23 0.98 ± 0.26 0.0426

Cerebrovascular CO2-reactivity (% increase in MFV)

32.8 ± 16.5 34.6 ± 15.6 33.2 ± 16.2 NS

Chap

ter 2

.1

24

total serum cholesterol

Per mmol increase in total serum cholesterol, MFV increased by 2.5 cm/s (95% confidence

interval 1.4 to 3.6, p<0.0001), but not after adjustment for age and sex. The cerebrovascular

CO2-reactivity decreased significantly with increasing total serum cholesterol. This was

observed after adjustment for remaining vascular risk factors. Twenty-five percent of the

patients were using cholesterol lowering drugs (statins) at inclusion in the study. We observed

table 3 Relationship of major vascular risk factors with MFV, PI, and cerebral CO2-reactivity the MCA, measured by transcranial Doppler ultrasound. Unadjusted, linear regression analysis. Effect size per unit of risk factor has been given, with 95% confidence limits.

Mean flow velocity Mean PI Mean cerebrovascular CO2-reactivity

Age -4.0cm/s/10yrs(-5.0 to -3.1)

0.10/10yrs(0.08 to 0.11)

0.7%/10yrs(-0.4 to 1.9)

Male Sex -6.0 cm/s(-8.6 to -3.3)

0.04(-0.00 to 0.09)

- 0.1%(-3.2 to 3.1)

Current smoking 3.3 cm/s(0.5 to 6.2)

-0.06(-0.1 to -0.01)

- 1.9%(-5.1 to 1.4)

Hypertension -3.2 cm/s(-5.7 to -0.6)

0.06(0.02 to 0.10)

- 3.1%(-6.0 to -0.2)

Diabetes 4.0 cm/s(0.5 to 7.5)

0.07(0.01 to 0.12)

- 0.8%(-4.9 to 3.3)

Total serum cholesterol 2.5cm/s/mmol(1.4 to 3.6)

-0.01/mmol(-0.03 to 0.01)

- 1.3%/mmol(-2.6 to 0.0)

table 4 Relationship of major vascular risk factors with MFV, PI, and cerebral CO2-reactivity the MCA, measured by transcranial Doppler ultrasound. Linear regression analysis adjusted for age, sex, hypertension, diabetes, and total cholesterol. Mean cerebrovascular CO2-reactivity also adjusted for change in blood pressure during hypercapnia. Effect size per unit of risk factor has been given, with 95% confidence limits.

Mean flow velocitya Mean PIb Mean cerebrovascular CO2-reactivityc

Age -3.5cm/s/10yrs(-4.5 to -2.5)

0.08/10yrs(0.07 to 0.10)

1.1%/10yrs(-0.1 to 2.3)

Male Sex -2.9 cm/s(-5.5 to -0.3)

0.01(-0.03 to 0.04)

-0.9%(-4.2 to 2.4)

Current smoking 1.7 cm/s(-1.0 to 4.4)

-0.02(-0.06 to 0.02)

-2.5%(-5.8 to 0.9)

Hypertension -0.2 cm/s(-2.7 to 2.4)

-0.00(-0.04 to 0.03)

-4.1%(-7.3 to -1.0)

Diabetes 5.6 cm/s(2.1 to 9.1)

0.07(0.02 to 0.12)

-0.3%(-4.8 to 4.1)

Total serum cholesterol 2.4 cm/s/mmol(1.4 to 3.5)

-0.01/mmol(-0.03 to 0.00)

-1.3%/mmol(-2.6 to -0.0)

a. F=16.56, (prob>F)<.00001,b. F=24.47, (prob>F) <.00001.c. F= 2.15 (prob>F)=.0377


no statistically significant relationship of cholesterol lowering drugs with mean flow, mean

Cerebral CO2-reactivity or mean pulsatility index.

other confounding factors

Adjustment for blood pressure during TCD investigation did not change these figures signifi-

cantly. After exclusion of the 37 patients with carotid stenosis, flow measures and CO2 reactivity

did not change significantly.

Discussion

In this study, we found that cardiovascular risk factors for atherosclerosis were significantly

related to flow velocities in the large arteries in the brain in patients with a recent TIA or isch-

emic stroke. Blood flow velocity in the MCA decreases with age, and is lower in men than in

women. Blood flow velocity in the MCA increases with total serum cholesterol, and is increased

in diabetics compared to non-diabetics. Cerebrovascular CO2-reactivity is lower in hypertensive

patients and decreases with increasing total serum cholesterol.

Before our results can be accepted, some methodological issues need to be discussed.

Firstly, in our study 25% of the patients had an inadequate acoustical window. These patients

were predominantly elderly female patients. Although this proportion matches that of other

studies,4,12,13 it implies that our findings are not representative for the entire population of

patients with recent TIA or stroke.

Secondly, we were not able to relate the results of Doppler ultrasound to other imaging

techniques, such as digital subtraction angiography or MR or CT angiography, which could

have corroborated our results. On the other hand, flow velocity and CO2 reactivity is deter-

mined by exactly the part of the intracranial vasculature that cannot be visualized by MR or CT

angiography. Thirdly, we calculated the cerebrovascular CO2 reactivity as the relative increase

in MFV in the MCA during hypercapnia. Most studies have used the percentage increase in

MFV per kPa CO2 rise in end-tidal CO2. Calculating the cerebrovascular CO2 reactivity per kPa

increase in end tidal CO2 should preferably be done because the MFV is dependent on the

end-tidal CO2.14 The relationship between the percentages administered CO2 and increase in

MFV is not linear, but is S-shaped, and a maximum increase in MFV is only reached after at

least 8% CO2.15 Calculating the increase of the MFV per increase in kPa CO2 would therefore

enhance the relationship with other (vascular risk) factors. In our study, however, end-tidal CO2

measurements failed in substantial number of patients due to technical limitations. Despite the

fact that we calculated the cerebral CO2 reactivity as the relative increase in MFV in the MCA,

and not the relative increase in MFV in the MCA per kPa rise in end-tidal CO2, the relationship

of hypertension and cholesterol with the cerebral CO2 reactivity was statistically significant.

Chap

ter 2

.1

26

Age- and sex-related differences in cerebral blood flow velocity have been reported previously

in population-based studies,10 in healthy volunteers14,16,17 and in patients with a previous neu-

rological event.8 The decline in MFV with increasing age is probably caused by flow reduction

in the MCA 8. Hormonal effects may play an important role in the difference in flow velocities in

the MCA between men and women under the age of 60 years.18 Gender-related differences in

MCA diameter could also play a role in this observed difference in flow velocities between men

and women.19 This gender-difference is consistently observed in patients at a younger age,

but not in elderly patients.8,10,14 Since the vessel diameter is not age-related, this probably only

plays a minor role in the observed difference in flow velocity. Moreover, Kastrup et al.20 have

reported a difference in cerebrovascular CO2 reactivity between patients with and patients

without hormonal replacement therapy: in patients with hormonal replacement therapy, the

cerebrovascular CO2 reactivity was higher than in patients without hormonal replacement

therapy. We could not make this distinction in our study, since very few patients received

hormonal replacement therapy. However, in our study no difference in cerebrovascular CO2

reactivity was found between premenopausal women and postmenopausal women.

Interestingly, the risk factors for atherosclerosis did not have a unidirectional relation with the

cerebral flow velocities. Age and sex showed inverse relations with the flow velocity parameters

in the MCA, whereas cholesterol level showed a positive relation with the flow velocity param-

eters in the MCA. This may be explained by the fact that hypercholesterolemia is associated

with increased peripheral vascular resistance, which can lead to increased cerebral flow velocity

in the MCA.21

It is likely that the relationship between hypertension and cholesterol on the one hand and

decreased cerebrovascular CO2 reactivity on the other reflects the presence of small vessel

disease. The relationship between small vessel disease and hypertension has been well estab-

lished.22 An impaired cerebrovascular CO2 reactivity has previously been associated with small

vessel disease or lacunar infarction.1,23-25 No interaction with statin treatment was noted.

Our results indicate that the cerebral flow velocity in the MCA is influenced by multiple interact-

ing factors. This implies that in future studies of TCD parameters as a prognostic or diagnostic

factor in patients with stroke or TIA, ultrasound findings will have to be adjusted for age, sex,

diabetes, total serum cholesterol level, and possibly also for hypertension.


reFerences

1. de Leeuw FE, de Groot JC, Oudkerk M, Witteman JC, Hofman A, van Gijn J, Breteler MM. Hypertension and cerebral white matter lesions in a prospective cohort study. Brain 2002;125:765-72.

2. Vermeer SE, Den Heijer T, Koudstaal PJ, Oudkerk M, Hofman A, Breteler MM. Incidence and risk factors of silent brain infarcts in the population-based Rotterdam Scan Study. Stroke 2003;34:392-6.

3. Amarenco P, Lavallee P, Touboul PJ. Statins and stroke prevention. Cerebrovasc Dis 2004;17 Suppl 1:81-8.:81-8.

4. Grolimund P, Seiler RW, Aaslid R, Huber P, Zurbruegg H. Evaluation of cerebrovascular disease by combined extracranial and transcranial Doppler sonography. Experience in 1,039 patients. Stroke 1987;18:1018-24.

5. Aaslid R, Markwalder TM, Nornes H. Noninvasive transcranial Doppler ultrasound recording of flow velocity in basal cerebral arteries. J Neurosurg 1982;57:769-74.

6. Bishop CC, Powell S, Rutt D, Browse NL. Transcranial Doppler measurement of middle cerebral artery blood flow velocity: a validation study. Stroke 1986;17:913-5.


8. Grolimund P, Seiler RW. Age dependence of the flow velocity in the basal cerebral arteries--a transcra-nial Doppler ultrasound study. Ultrasound Med Biol 1988;14:191-8.


10. Bakker SL, de Leeuw FE, Den Heijer T, Koudstaal PJ, Hofman A, Breteler MM. Cerebral haemodynamics in the elderly: the rotterdam study. Neuroepidemiology 2004;23:178-84.

11. Diehl RR, Berlit P. Dopplerfunktionstests. Funktionelle Dopplersonographiein der Neurologie. Berlin: Springer; 1996.

12. Itoh T, Matsumoto M, Handa N, Maeda H, Hougaku H, Hashimoto H, Etani H, Tsukamoto Y, Kamada T. Rate of successful recording of blood flow signals in the middle cerebral artery using transcranial Doppler sonography. Stroke 1993;24:1192-5.


14. Vriens EM, Kraaier V, Musbach M, Wieneke GH, van Huffelen AC. Transcranial pulsed Doppler measure-ments of blood velocity in the middle cerebral artery: reference values at rest and during hyperventi-lation in healthy volunteers in relation to age and sex. Ultrasound Med Biol 1989;15:1-8.

15. Ringelstein EB, Sievers C, Ecker S, Schneider PA, Otis SM. Noninvasive assessment of CO2-induced cerebral vasomotor response in normal individuals and patients with internal carotid artery occlu-sions. Stroke 1988;19:963-9.

16. Nagai Y, Kemper MK, Earley CJ, Metter EJ. Blood-flow velocities and their relationships in carotid and middle cerebral arteries. Ultrasound Med Biol 1998;24:1131-6.

17. Krejza J, Mariak Z, Walecki J, Szydlik P, Lewko J, Ustymowicz A. Transcranial color Doppler sonography of basal cerebral arteries in 182 healthy subjects: age and sex variability and normal reference values for blood flow parameters. AJR Am J Roentgenol 1999;172:213-8.

Chap

ter 2

.1

28

18. Matteis M, Troisi E, Monaldo BC, Caltagirone C, Silvestrini M. Age and sex differences in cerebral hemodynamics: a transcranial Doppler study. Stroke 1998;29:963-7.

19. Muller HR, Brunholzl C, Radu EW, Buser M. Sex and side differences of cerebral arterial caliber. Neuro-radiology 1991;33:212-6.

20. Kastrup A, Dichgans J, Niemeier M, Schabet M. Changes of cerebrovascular CO2 reactivity during normal aging. Stroke 1998;29:1311-4.

21. Rubba P, Faccenda F, Di Somma S, Gnasso A, Scarpato N, Iannuzzi A, Nappi G, Postiglione A, De Divitiis O, Mancini M. Cerebral blood flow velocity and systemic vascular resistance after acute reduction of low-density lipoprotein in familial hypercholesterolemia. Stroke 1993;24:1154-61.

22. Tanizaki Y, Kiyohara Y, Kato I, Iwamoto H, Nakayama K, Shinohara N, Arima H, Tanaka K, Ibayashi S, Fujishima M. Incidence and risk factors for subtypes of cerebral infarction in a general population: the Hisayama study. Stroke 2000;31:2616-22.



25. Vermeer SE, Koudstaal PJ, Oudkerk M, Hofman A, Breteler MM. Prevalence and risk factors of silent brain infarcts in the population-based Rotterdam Scan Study. Stroke 2002;33:21-5.

chapter 2.2Skull thickness and bone density as predictors

of an inadequate acoustical temporal bone window in transcranial Doppler ultrasound

A.D. Wijnhoud

M. Franckena

A. Van der Lugt

P.J. Koudstaal

D.W.J. Dippel

Ultrasound Med Biol. 2008;34:923-9.

Chap

ter 2

.2

32

AbstrAct

Transcranial Doppler (TCD) ultrasonography may provide important diagnostic and prognostic

information in patients with ischemic stroke or transient ischemic attack. TCD also enhances

the effect of thrombolytic treatment in patients with acute stroke. In some patients, especially

elderly women, TCD cannot be performed because of temporal bone window failure (WF). We

investigated whether skull thickness or bone density on computed tomography scans predicts

WF. In 182 patients with a transient ischemic attack or minor ischemic stroke, skull thickness and

bone density measurements were made at the level of the temporal bone window. Multiple

logistic regression analysis was used to relate independent variables to WF, and to adjust the

estimates for possible confounding factors. TCD signals were absent on the symptomatic side

in 22 female and 11 male patients (18%). Both skull thickness and radiodensity at the level of

the temporal bone window were strongly related to WF as well as age and female gender. After

adjustment according to age and gender, skull thickness at the temporal bone window was an

independent prognostic factor of WF (Odds Ratio: 2.3 per mm increase in skull thickness, 95%

C.I.: 1.4 to 3.8). Radiodensity of the temporal bone decreased with age in women (-52 HU per

10 years over 50 years of age, 95% C.I.: -73 to -30), but in men (-10 HU per 10 years over 50 years

of age, 95% C.I.: -33 to 13), no statistically significant association was observed. We computed

probabilities of WF for each patient individually. With a probability cut point of 50%, 33% of the

patients with WF and 97% of the patient without WF were correctly identified. The area under

the ROC curve of this simple prediction model including age, gender, and skull thickness was

0.88; the area under the ROC curve of a gender-stratified model including age, skull thickness,

and radiodensity was 0.90. This difference was not statistically or clinically significant p=0.13).

WF is more common in women, because density of the temporal bone in elderly women is

low. Absence of WF can be predicted by a combination of three simple parameters: skull thick-

ness, age, and gender. This may help to select patients with ischemic stroke for diagnostic TCD

screening and to facilitate targeted delivery of ultrasound-enhanced thrombolysis.

Role of skull thickness and bone density in window failure 33

introDuction

Transcranial Doppler (TCD) ultrasonography can be used to assess intracranial blood flow in a

non-invasive way. It may provide important diagnostic and prognostic information in patients

with a recent transient ischemic attack (TIA), or minor stroke, and in patients with acute

ischemic stroke 1,2. Furthermore, experimental studies have demonstrated that reperfusion is

reached more often and more quickly when intravenous thrombolytic agents are combined

with a transcranial ultrasound beam directed at the thrombus 3,4. More recently, several clinical

observations and one clinical phase II trial (CLOTBUST) showed that ultrasound enhances the

effect of thrombolytic agents on reperfusion in patients with an acute cerebral infarction in the

middle cerebral artery territory. Whether ultrasound enhanced thrombolysis improves outcome

in patients with acute ischemic stroke is currently being investigated in a phase III clinical trial

(CLOTBUST II) 5,6. Usually, TCD monitoring can be easily and quickly performed , but in 5–37%

of the patients, however, no adequate Doppler signal can be found because of an inadequate

acoustic temporal window or window failure (WF) 7-9. TCD can be a time-consuming investiga-

tion in case of an inadequate signal in patients with insufficient temporal bone window.

The temporal bone window is the thinnest area of the lateral skull located closest to the ear.

It allows for an ultrasound beam to invade and be reflected. Numerous studies have reported

that an inadequate temporal bone window is more common in older women 10-12, and in non-

Caucasians8. Moreover, an inadequate temporal bone window is also related to thickening of

the skull 13-15.

We studied the relationship of skull thickness and density of the temporal bone with WF to

determine if WF can be predicted easily and accurately.

methoDs

study population

We retrospectively studied computed tomography (CT) scans of patients from a prospective

cohort study in which we investigated the diagnostic and prognostic value of TCD in patients

with a recent TIA or ischemic non-disabling stroke. Inclusion criteria were a recent (<6 months)

TIA or non-disabling ischemic stroke. Patients had to be over 18 years of age, and had to give

informed consent to be included in this study. The study was approved by the Medical Ethics

Committee and Review Board of the Erasmus MC in Rotterdam, The Netherlands. Patients had

to be independent in most activities in daily living, corresponding with grade 3 or better on the

modified Rankin scale 16,17.

All patients underwent TCD examination and received a routine check up, including a com-

puted tomography (CT) scan, neurological and physical examination, routine laboratory tests,

and a duplex of the carotid arteries in case of an anterior circulation stroke or TIA.

Chap

ter 2

.2

34

tcD examination

TCD examination was performed with a Multidop X4 (DWL, Sipplingen, Germany) using a 2

MHz handheld probe. Power was set at 147 mW and increased if necessary to 200 mW. Since the

TCD examination was originally performed for different purposes than to study the relationship

between CT measurements and WF, we searched for a signal of the middle cerebral artery (MCA)

on both symptomatic and asymptomatic side at a depth ranging from 41 – 65 mm for at least

10 minutes. A signal was considered adequate if an envelope could be visualized around the

Doppler spectrum for the calculation of the mean, peak and end-diastolic velocities (Figure 1).

WF was only considered when neither an MCA signal nor any other arterial signal could be

visualized adequately in order to rule out an MCA occlusion. We did not use any contrast agents

during the TCD examination. All TCD-examinations were performed by one investigator (A.W.),

who was blinded to the results of the measurements performed on the CT-scans.

Quantitative ct scan measurements

All CT scans were made on two Philips Somatom Plus 4 CT scanners (Philips BV, The Nether-

lands) in Erasmus Medical Center Rotterdam from April 1998 to March 2000. All CT scans were

performed as part of routine patient care. The CT scans were made with a slice thickness of 5

mm. The CT scans were recovered from the digital archives in our hospital.

We measured skull thickness and radiodensity at a region of interest (ROI). We defined our

ROI in the slice above the sella turcica just above the external meatus. The circular ROI was

positioned at the level of the temporal bone window at the thinnest part of the skull. Both skull

thickness and radiodensity were measured in the same ROI. Radiodensity measurements were

performed by means of a Siemens Magic View® workstation (Siemens AG, Germany). After des-

ignating the ROI we calculated the mean radiodensity in Hounsfield Units (HU) for the ROI. To

eliminate the contribution of non-bone elements in the ROI and the influence of partial volume

effects in measuring the radiodensity, a cut point was determined at a level halfway between

Figure 1: Image of an adequate transcranial Doppler ultrasonography signal of the MCA with a mean velocity of 47.1 m/s, peak-systolic flow velocity of 69 cm/s, and an enddiastolic flow velocity of 33 cm/s.


the maximum and the minimum radiodensity in the ROI. This means that all components with

radiodensities below the cut point were discarded in the second measurement, only leaving

the bony parts of the skull to be taken into account when calculating the radiodensity of the

temporal bone window.

Skull thickness was measured by means of a Philips Easy Vision® workstation (Philips BV, The

Netherlands). The measurements were carried out three times on either side of the skull, all

three close to each other inside the region of interest. On each side three lines were drawn

from the outside of the skull to the inside at our ROI and the computer made graphs of the

distribution of radiodensities along the lines that were drawn. The width of the bony skull was

measured after applying this cut point to distinguish between bone and soft tissue. The mean

of these three measurements was calculated. One observer (M.F.) performed the measure-

ments on the CT scans. This observer was blinded to the presence or absence of an adequate

TCD signal.


We analysed the temporal bone window on the symptomatic side in patients. The analysis was

carried out with STATA 8 software (Stata Corporation, College Station, Texas USA). Differences

between patients with WF and patients without WF were analysed using parametric tests or

chi-square tests. A p-value below 0.05 was considered statistically significant. Multiple logistic

regression analysis was used to relate independent variables to the occurrence of WF, and to

adjust for possible confounding factors, such as age and gender. We evaluated the relation-

ship between WF and radiodensity and thickness of the temporal bone with a multiple logistic

regression model adjusting for age and gender. We then created an interaction factor (skull

thickness x radiodensity) to study if thickness and density were dependent on each other, i.c.

if thicker bones had less radiodensity. For prediction, two models were created: one with three

simple parameters including age, gender, and skull thickness, and a gender-specific model

including age, skull thickness and radiodensity. The performance of these models for predic-

tion of WF was assessed by comparing the area under the receiver operating characteristics

(ROC) curve. The ROC curve plots 1-specificity versus sensitivity for WF. The area under the ROC

curve was calculated to assess the regression model’s performance in distinguishing between

the presence and the absence of WF. An area of 1.0 represents a perfect test, whereas an area

of 0.5 indicates a test with no discriminatory power. The area under the ROC curve is especially

meaningful for comparing different tests or prediction models, as we did.18. The ROC curve was

constructed after computing probabilities for each patient with the multiple logistic regression

model.

Chap

ter 2

.2

36

resuLts

285 consecutive patients were eligible for inclusion in this study. In 79 patients, the CT-images

were not available at the time of study. In 6 patients, scans were made on a different type of CT

scanner, and in 8 patients, the CT scan image was technically inadequate. This left 182 patients

for analysis. Patients in whom the CT scan was not available for analysis did not differ from

included patients with regard to age, gender, occurrence of WF.

WF was present in 33 (18%) patients. Patients with WF were older than patients without WF,

72.4 ± 9.3 vs. 58.8 ± 13.9 years (mean ± SD) . WF was not present in patients under 50 years of

age. Patients with WF were more often female than patients without WF (67% vs. 34%, p=0.001)

(Table 1).

The mean skull thickness in the study population was 3.1 ± 0.9 mm (mean ± SD). The mean

radiodensity at the temporal bone window on the symptomatic side was 1001 ± 163 HU (mean

± SD) (Table 1). Skull thickness was related to age: 0.14 mm increase per 10 years over 50 years

of age, 95% C.I.: 0.05 to 0.23, but not to gender: 3.2 ± 0.9 mm in women vs. 3.1 ± 1.0 mm in men.

Radiodensity of the temporal bone decreased statistically significant with higher age in women

(-52 HU per 10 years over 50 years of age, 95% C.I.: -73 to -30), but not in men (-10 HU per 10

years over 50 years of age, 95% C.I.: -33 to 13) (Fig 2). Ethnicity was neither related to WF nor to

skull thickness.

In patients with WF, skull thickness was 3.8 ± 1.1 mm compared to 3.0 ± 0.8 mm (mean ± SD)

in patients without WF (p<0.001). Radiodensity of the temporal bone was lower in patients with

WF (943 ± 146 HU) than in patients without WF (1014 ± 164 HU (mean ± SD), p=0.022) (Table 1).

table 1: Baseline characteristics

Overall WF No WF

No. of patients 182 (100%) 33 (18%) 149 (82%)

Baseline

Age (yrs), mean ± SD 61.2 ± 14.2 72.4 ± 9.3 58.8 ± 13.9 p<0.000

Male gender 109 (59.9 %) 11 (33%) 98 (66%) p=0.001

Caucasian Race 162 (90 %) 30 (91%) 132 (89%) NS

Risk factors

Hypertension 76 (41.8%) 17 (52%) 59 (40%) NS

Diabetes Mellitus 21 (11.7%) 5 (15%) 16 (11%) NS

Hyperlipidemia 54 (30.9%) 10 (31%) 44 (31%) NS

Previous MI 22 (12.3%) 5 (16%) 17 (12%) NS

Intermittent claudication 17 (9.5%) 1 (3%) 16 (11%) NS

CT measurements

Skull thickness (mm), mean ± SD 3.1 ± 0.9 3.8 ± 1.1 3.0 ± 0.8 p<0.000

Radiodensity (HU), mean ± SD 1001 ± 163 943 ± 146 1014 ± 164 p=0.022


After adjustment for age and gender, the relationship between skull thickness and WF did not

change (Table 2). Radiodensity of the skull on the symptomatic side, however, was no longer

related to WF after adjustment for age and gender (Table 2). We also studied the possibility

of interaction between skull thickness and radiodensity of the temporal bone by creating a

new variable (skull thickness × radiodensity of the temporal bone). This interaction factor was

related to WF, but not after adjustment for age and gender (Table 2).

We then constructed multiple logistic regression models for men and women separately,

that included age, skull thickness, and radiodensity of the temporal bone, because radioden-

sity was very strongly related to age in women. In men, skull thickness, as well as radiodensity

was related to WF (Table 3). In women, age and skull thickness were related to WF, whereas

radiodensity was not (Table 3).

2,60

2,80

3,00

3,20

3,40

3,60

3,80

4,00

Skul

l thi

ckne

ss s

ympt

sid

e (m

m)

Men

Women

2,00

2,20

2,40

2,60

< 50 50 - 60 60 - 70 70 - 80 > 80

Skul

l thi

ckne

ss s

ympt

sid

e (m

m)

Age (years)A

800

900

1000

1100

1200

radi

oden

sity

sym

pt s

ide

HU

(HU

)

Men

Women

600

700

< 50 50 - 60 60 - 70 70 - 80 > 80

radi

oden

sity

sym

pt s

ide

HU

Age (years)B

Figure 2: Skull thickness (A) and radiodensity (B) at the level of the temporal bone window per age group for men and women.

Chap

ter 2

.2

38

We calculated probabilities of WF for each patient individually, by means of a multiple

regression model including age, gender, and skull thickness. In this model, age, sex, and skull

thickness were independently related to WF (Table 4). Female gender was the strongest predic-

tor of the presence of WF. With a probability cut point of 50%, 33% of the patients with WF were

correctly identified as having WF, and 97% of those without WF were correctly identified as

having no WF. The positive predictive value with this probability cut point was 69%, the nega-

tive predictive value was 87%. With a probability cut point of 90% the positive predictive value

increased to 100%, but the negative predictive value was 83%. The area under the ROC curve of

the simple prediction model including age, gender, and skull thickness was 0.88; the area under

table 2: Odds ratios for window failure for skull thickness (A) and radiodensity of the temporal bone (B).

A Unadjusted Adjusted for age and gender

Adjusted for age, gender, and radiodensity

Adjusted for age, gender, radiodensity and the interaction factor (skull thickness * density)†

Skull thickness‡

OR (95% C.I.) 2.37 (1.58–3.57) 2.33 (1.44-3.79) 2.49 (1.49-4.17) 3.71 (0.28-49.0)

† Odds ratio for WF for the interaction factor (skull thickness * density) was 1.00 (95% C.I.: 0.99-1.01) in this model‡ per mm increase in skull thickness

B Unadjusted Adjusted for age and gender

Adjusted for age, gender, and skull thickness

Adjusted for age, gender, skull thickness, and the interaction factor (skull thickness * density)

Radiodensity§

OR (95% C.I.) 0.76 (0.63-0.98) 1.00 (0.76-1.32) 0.86 (0.64-1.16) 0.99 (0.38-2.61) †

† Odds ratio for WF for the interaction factor (skull thickness * density) was 1.00 (95% C.I.: 0.99-1.01) in this modelc§ per 100 HU increase in radiodensity of the temporal bone

table 3: Odds ratios for window failure, based on a multiple logistic regression models of age, skull hickness, and radiodensity, for men and women separately.

Window failure symptomatic side OR (95% CI)

Men Women

Age per 10 yrs over 50 yrs 1.71 (0.86 – 3.39) 4.08 (1.84 – 9.01)

Skull thickness per mm 3.58 (1.73 – 7.43) 2.42 (1.01 – 5.80)

Radiodensity per 100 HU 0.65 (0.44 – 0.93) 1.20 (0.79 – 1.83)

table 4: Odds ratios for window failure based on a logistic regression model of age, gender, and skull thickness.

Window failure symptomatic side OR (95% CI)

Age per 10 yrs over 50 yrs 2.58 (1.63 – 4.07)

Female gender 5.94 (2.21 – 15.9)

Skull thickness per mm 2.33 (1.44 – 3.79)


the ROC curve of a gender-specific model including age, skull thickness, and radiodensity was

0.90. This difference was not statistically or clinically significant p=0.13)

We calculated probability cut points of skull thickness for WF, as a function of age based on

the simple logistic regression model including age, sex, and skull thickness. These results are

shown in Figure 3. With this figure, estimation of the probability of WF for an individual patient

can be made. For example, in an eighty-year old male patient with a temporal bone thickness of

3.3 mm, the chance of WF would be less than 10% (black dot in Figure 3A). If this patient would

be female, the probability of WF would increase to approximately 80% (black dot in Figure 3B).

4

5

6

7

8

9

10

Skul

l thi

ckne

ss s

ympt

omat

ic si

de (m

m)

Men

>90%67-90%50-67%33-50%10-33%<10%

0

1

2

3

50 60 70 80 90

Skul

l thi

ckne

ss s

ympt

omat

ic si

de (m

m)

Age (years)

<10%

A

4

5

6

7

8

9

10

Skul

l thi

ckne

ss s

ympt

omat

ic si

de (m

m)

Women

>90%67-90%50-67%33-50%10-33%<10%

0

1

2

3

50 60 70 80 90

Skul

l thi

ckne

ss s

ympt

omat

ic si

de (m

m)

Age (years)

<10%

B

Figure 3: Dependency of cut points of skull thickness (mm) on age and gender to predict window failure with different probabilities for men (A) and for women (B). In women, the cut point is lower than in men. With this figure, estimation of the probability of WF for an individual patient can be made. For example, in an eighty-year old male patient with a temporal bone thickness of 3.3 mm, the chance of WF would be less than 10% (black dot in figure 2A). If this patient would be female, the probability of WF would increase to approximately 80%.

Chap

ter 2

.2

40

Discussion

Our study confirms that skull thickness at the level of the temporal window is related to

inadequacy of the ultrasound signal. Furthermore, skull thickness is more closely related to WF

than radiodensity of the temporal bone. A decreased radiodensity of the bone at the temporal

window was also related to WF, but not significantly so, after adjustment for age and gender.

Some methodological issues need to be discussed. First, selection bias could have occurred,

since skull thickness and radiodensity measures could not be carried out in all patients, as the

CT scan was not available for analysis at the time of our study. However, patients in whom

the CT scan was not available for analysis did not differ from included patients with regard to

age, gender, and occurrence of WF. We therefore think that the CT non-availability represents

random error and does not bias the results of our study. Secondly, we did not use any contrast

agents during TCD investigation. Contrast agents enhance assessment of intracranial cerebral

arteries, however, the original protocol for this study did not allow for use of contrast agents.

In our study, age and gender are strongly related to WF. This confirms the results of previ-

ous studies 7,8,19. We used a simple method to determine skull thickness and density of the

temporal bone window in vivo. Our observation that the temporal bone was thicker in women

than in men is in concordance with other studies 13,20. Skull thickness in relation to WF has been

measured in postmortem studies 21, and in clinical studies. 13,20. These studies have shown that

skull thickness is related to the presence of WF. This can probably be explained by the notion

that ultrasound is scattered by the cancellous bone in the diploe 22. Moreover, the thickness of

the cancellous bone is related to the presence of WF 21.

In our study, radiodensity of the temporal bone was related to age, but only in women.

Unadjusted, radiodensity was related to WF on the symptomatic side, but this relationship was

neutralized by female gender. We therefore conclude that the high incidence of WF in elderly

women is probably caused by loss of skull density. However, gender-stratified logistic regres-

sion models including radiodensity, did not predict WF more accurately than the simple logistic

regression model including age, gender, and skull thickness. Recently, Kwon et al. 20 have

described the relationship between inhomogeneity of temporal bone and WF. Most probably,

loss of density leads to energy loss due to scattering of the ultrasound beam, and therefore to

an inadequate Doppler signal 23 .

We showed that a simple logistic regression model of age, gender, and skull thickness could

predict absence of WF in nearly all patients correctly. The positive predictive value, however,

was only 69%, where 100% is desirable, since the percentage of false positive predictions

needs to be as low as possible. Our study results may be particularly helpful when ultrasound

enhanced thrombolysis has been proven to improve clinical outcome. CT measurements, that

take approximately 5 minutes of time, may be helpful in avoiding TCD measurements in patients

with a high probability of WF. This is important especially when this service is not available on

a 24-hour basis. If skull thickness were to be used as a screening test to identify patients with


probable bone window failure, then the cut point should depend on the disutility of missing

a patient with window failure and missing a patient without window failure. If both disutilities

are considered equal, then a cut point of 50% should suffice. If thrombolysis is proven to be

enhanced by TCD, and missing a patient without window failure is ten times worse that missing

one with window failure, then the cut point would be 90%. We chose 90% to estimate how

many patients should be screened. In our study, none of the men had a probability of more

than 90% of having window failure. This means that in practice, only women would have to be

screened for WF. No woman under 70 years of age had a probability of more than 90% of having

WF. Only 21 women in our study were older than 70 years of age, of whom 3 had a probability

of more than 90% of having WF, which means that the number needed to screen is 7 (female)

patients.

Our relatively large study provides quantitative estimates of the contribution of skull density

and thickness parameters to the occurrence of window failure. We conclude that both thick-

ness and density of the temporal bone are related to the presence of WF, but that skull density

does not independently predict WF. Absence of WF can be predicted accurately in nearly all

patients with ischemic stroke or TIA by means of three simple parameters: skull thickness, age

and gender. This may help to select patients for diagnostic TCD screening and perhaps in the

near future, to facilitate targeted delivery of ultrasound-enhanced thrombolysis.

Chap

ter 2

.2

42

reFerences

1. Comerota AJ, Katz ML, Hosking JD, Hashemi HA, Kerr RP, Carter AP. Is transcranial Doppler a worth-while addition to screening tests for cerebrovascular disease? J Vasc Surg 1995;21:90-5.

2. Wijnhoud AD, Koudstaal PJ, Dippel DW. Relationships of transcranial blood flow Doppler parameters with major vascular risk factors: TCD study in patients with a recent TIA or nondisabling ischemic stroke. J Clin Ultrasound 2006;34:70-6.

3. Francis CW, Suchkova VN. Ultrasound and thrombolysis. Vasc Med 2001;6:181-7.

4. Francis CW, Blinc A, Lee S, Cox C. Ultrasound accelerates transport of recombinant tissue plasminogen activator into clots. Ultrasound Med Biol 1995;21:419-24.

5. Alexandrov AV, Demchuk AM, Felberg RA, Christou I, Barber PA, Burgin WS, Malkoff M, Wojner AW, Grotta JC. High rate of complete recanalization and dramatic clinical recovery during tPA infusion when continuously monitored with 2-MHz transcranial doppler monitoring. Stroke 2000 Mar ;31 (3 ):610 -4 2000;31:610-4.

6. Alexandrov AV, Molina CA, Grotta JC, Garami Z, Ford SR, varez-Sabin J, Montaner J, Saqqur M, Demchuk AM, Moye LA, Hill MD, Wojner AW. Ultrasound-enhanced systemic thrombolysis for acute ischemic stroke. N Engl J Med 2004;351:2170-8.






12. Hoksbergen AW, Legemate DA, Ubbink DT, Jacobs MJ. Success rate of transcranial color-coded duplex ultrasonography in visualizing the basal cerebral arteries in vascular patients over 60 years of age. Stroke 1999;30:1450-5.

13. Jarquin-Valdivia AA, McCartney J, Palestrant D, Johnston SC, Gress D. The thickness of the temporal squama and its implication for transcranial sonography. J Neuroimaging 2004;14:139-42.

14. Bruno A, Biller J, Silvidi JA. A reason for failure to obtain transcranial Doppler flow signals. Hyperosto-sis of the skull [letter]. Stroke 1988;19:274.

15. Grolimund P. Transmission of ultrasound through the temporal bone. In: Aaslid R, editor. Transcranial Doppler sonography.New-York: Springer-Verlag; 1986. p. 10-21.

16. van Swieten JC, Koudstaal PJ, Visser MC, Schouten HJ, van Gijn J. Interobserver agreement for the assessment of handicap in stroke patients. Stroke 1988;19:604-7.


17. Bamford JM, Sandercock PA, Warlow CP, Slattery J. Interobserver agreement for the assessment of handicap in stroke patients. Stroke 1989;20:828.

18. Vergouwe Y, Steyerberg EW, Eijkemans MJ, Habbema JD. Validity of prognostic models: when is a model clinically useful? Semin Urol Oncol 2002;20:96-107.

19. Halsey JH. Effect of emitted power on waveform intensity in transcranial Doppler. Stroke 1990;21:1573-8.

20. Kwon JH, Kim JS, Kang DW, Bae KS, Kwon SU. The thickness and texture of temporal bone in brain CT predict acoustic window failure of transcranial Doppler. J Neuroimaging 2006;16:347-52.

21. Kollar J, Schulte-Altedorneburg G, Sikula J, Fulesdi B, Ringelstein EB, Mehta V, Csiba L, Droste DW. Image quality of the temporal bone window examined by transcranial Doppler sonography and correlation with postmortem computed tomography measurements. Cerebrovasc Dis 2004;17:61-5.

22. Fry FJ, Barger JE. Acoustical properties of the human skull. J Acoust Soc Am 1978;63:1576-90.

23. White DN, Curry GR, Stevenson RJ. The acoustic characteristics of the skull. Ultrasound Med Biol 1978;4:225-52.

chapter 2.3Diagnosis of ischemic stroke subtype and potential cardiac sources of embolism by

transcranial Doppler ultrasonography. A systematic review

A.D. Wijnhoud

P.J. Koudstaal

D.W.J. Dippel

Chap

ter 2

.3

46

AbstrAct

Background: High Intensity Transient Signals (MES) in Transcranial Doppler ultrasonography

(TCD) monitoring may indicate micro-thromboembolism in patients with recent ischemic

stroke or TIA. However, it is unclear whether TCD monitoring for MES is helpful in the diagnosis

of a potential cardiac source of embolism (PCSE) and of stroke subtype (i.e. small-vessel disease

or not).

Methods: We searched NLM Medline, Embase and cross-references in articles for published

studies on TCD MES monitoring in patients with a TIA or ischemic stroke. Of each study we

computed the sensitivity and specificity of MES for stroke subtype and for a PCSE. Next, we

combined data from each study into a summary receiver operating characteristic (sROC) curve.

We took into account the clinical characteristics of each study population, method of MES

detection and whether technical details of TCD examination were reported. We contrasted the

results of the meta-analysis with the findings in our own study.

Results: Thirteen studies were identified. There was heterogeneity in study design and methods

between the studies, and technical details were not always reported in detail. Nevertheless, our

analysis showed that in the nine studies that used a well-defined reference test for ischemic

stroke subtype the specificity of TCD for non-lacunar stroke was 0.90, and sensitivity was 0.76.

Sensitivity for PCSE in the eight studies that used a well-defined reference test was 0.74 and

specificity was 0.65 at the optimal point of the sROC curve. In our own study sensitivity for

stroke subtype was 0, and specificity was 0.91. For PCSE sensitivity was 0, and specificity was

0.95. Sensitivity was low because this was not performed in the acute phase.

Conclusions: The sensitivity and specificity of MES detection with transcranial Doppler ultra-

sound in the diagnosis of PCSE is not high enough to recommend its use for screening prior to

more invasive diagnostic investigations, such as transesophageal echocardiography. However,

results in patients with a recent stroke, a confident diagnosis of non-lacunar stroke can be made

when MES are detected with TCD.

Diagnosis of stroke subtype and cardio-embolism with TCD 47

introDuction

Deciding whether a patient had a lacunar or a non-lacunar stroke can be quite difficult. Many

patients had a short attack, have residual symptoms that are not very helpful, and their CT or

MRI may be normal.1 Additional diagnostic information that helps to determine stroke subtype

in such patients could be helpful. The “micro-embolic signals” (MES), detected by transcranial

Doppler ultrasonography (TCD), may help in distinguishing non-lacunar (thromboembolic)

from lacunar stroke. TCD could perhaps also be helpful in the detection of a potential cardiac

source of embolism (PCSE). A truly non-invasive diagnostic investigation that could be used to

identify patients, who will not benefit from transesophageal echocardiography (TEE), would be

most welcome.

Monitoring for microembolic signals by means of TCD is not a standard investigation in

stroke patients, and its potential clinical usefulness is unclear. In patients with a recent stroke or

transient ischemic attack, MES are not uncommon.2-4 Several studies have shown that MES are

more often present in patients with a cortical stroke2 and in patients with PCSE.5 However, the

sensitivity and specificity of TCD (i.e. MES monitoring) for non-lacunar stroke or PCSE in these

studies varied greatly. Although most studies used similar criteria for MES, comparison of the

data is made difficult by differences in important other variables such as detection threshold,6-8

method of MES-detection (automated, human observer, or a combination),7-9 or time window

between stroke and TCD investigation.10 This diversity makes it difficult to draw conclusions

about the diagnostic value of TCD in patients who had an ischemic stroke or TIA.

The purpose of this study was to determine the diagnostic value of TCD MES monitoring

in patients with transient ischemic attack or ischemic stroke regarding stroke subtype and

the presence of a PCSE. We therefore compared the data in a summary receiver operating

characteristic curve as suggested by Moses et al.11 Finally, we compared the findings from our

systematic review with the results of the Rotterdam TCD study, a cohort study of the prognostic

and diagnostic value of TCD in 592 patients with a recent TIA or stroke.

Chap

ter 2

.3

48

methoDs

selection of relevant studies

We searched NLM Medline, Embase, and cross references in articles for published studies on

TCD MES monitoring in patients with a recent TIA or ischemic stroke. We used the following

search keys: [(TIA OR stroke) AND (TCD OR transcranial Doppler ultrasonography)]. The articles

were selected on the basis of their title and the information in the abstract. To be included in

this review, the study should concern a series of patients with stroke or TIA who underwent

TCD monitoring for MES. The results of the TCD investigation should be compared with a “gold

standard” or “reference” diagnosis.

Definitions

Small vessel disease was defined according to the TOAST criteria:12 a lacunar syndrome with a

normal CT, or as a CT showing a relevant lacunar infarct sized 1.5 cm in diameter or less without

another cause of the stroke.

We defined PCSE according to the TOAST criteria,12 and included high risk sources of embo-

lism, such as atrial fibrillation, recent (<4 weeks) myocardial infarction, sick sinus syndrome,

prosthetic cardiac valves and left atrial appendage or ventricular thrombus, and medium risk

sources, such as patent foramen ovale, left atrial or ventricular aneurysm, mitral valve prolaps,

old (1-6 months) myocardial infarction and atrial or ventricular septal defect. Preferably, the

diagnosis of PCSE should have been confirmed by echocardiography.

criteria for inclusion of studies

We checked whether the study population and relevant clinical characteristics was described

adequately to evaluate the diagnostic accuracy and reproducibility.13 Relevant characteristics

that were considered in this review were time since onset of stroke, its vascular distribu-

tion, the presumed mechanism, especially whether the infarct was considered to be due to

small vessel occlusion or not, age, and sex distribution. These characteristics may affect the

accuracy of TCD: the test may perform well in certain subgroups and poorly in others, despite

reasonable average values of accuracy. Verification bias occurs when patients with positive (or

negative) diagnostic tests preferentially receive verification by the reference test. For example,

patients with MES may have a higher chance of being referred for a cardiologic consultation

and echocardiography than patients without MES. We noted whether patients had undergone

thransthoracic or transesophageal echocardiography. We tried to estimate from the studies the

ratio of the verification rate in patients with MES and the verification rate in patients without

MES. Review bias can be introduced when either the diagnostic test or the reference procedure

is assessed without objectivity in the interpretation. We noted whether the TCD examination

was carried out without knowledge of the results of the reference test or other investigations. In


addition, we checked whether the reference test (for example echocardiography or a CT scan)

was interpreted without knowledge of the results of the TCD-investigation.

tcD investigation: technical aspects.

MES were defined as transient Doppler microembolic signals, usually lasting less than 300 mil-

liseconds. The amplitude of the Doppler microembolic signal should be at least 3 decibel (dB)

higher than that of the background blood flow signal, within the appropriate dynamic range

of bi-directional Doppler equipment. In addition, MES are unidirectional within the Doppler

velocity spectrum and accompanied by a “snap,” “chirp,” or “moan” on the audible output.8 We

checked if a fixed detection threshold was used in each study.

We checked whether studies reported parameters that are likely to influence the sensitivity

and specificity of TCD, as recommended by the International Consensus Committee on Micro-

embolus Detection.8 These parameters include ultrasound device, insonated artery, insonation

depth, algorithms for signal intensity measurement, detection threshold, axial extension of

sample volume, fast Fourier transform (FFT) size (number of points used), FFT length (time), FFT

overlap, transmitted ultrasound frequency, and recording time.

method of quantitative analysis

We computed for each study the sensitivity and specificity for non-lacunar stroke and PCSE

after translation of the results in a simple 2´2 table. Sensitivity for non-lacunar stroke was com-

puted by the number of MES-positive patients with a non-lacunar stroke divided by the total

number of patients with a non-lacunar stroke. Sensitivity for PCSE was taken as the number

of MES-positive patients with a PCSE divided by the total number of patients with a PCSE.

Thus, sensitivity was estimated by taking the probability of a positive test in patients with the

condition of interest; this will be referred to as the True Positive Rate (TPR). The specificity for

non-lacunar stroke was defined as the number of MES-negative patients with a lacunar stroke

divided by the total number of patients with a lacunar stroke. The specificity for PCSE was

assessed as the number of MES-negative patients without a PCSE divided by the total number

of patients without a PCSE. Similarly, 1-specificity represents the probability of a positive test in

patients without the condition or disease of interest; this will be referred to as the False Positive

Rate (FPR). The sensitivity and specificity for PCSE was determined after exclusion of patients

with a significant carotid stenosis (>50% by duplex ultrasound), since carotid stenosis can be

an important source of MES.14-17

TPR and FPR are not independent of each other since both may increase or decrease when

the threshold for a positive test, i.e. dB threshold, is changed. TPR can be plotted against FPR

in a receiver operating characteristic (ROC) curve. An ROC curve is a path in the unit square,

rising from the lower left corner, where TPR and FPR are both zero, to the upper right corner,

where TPR and FPR are both one. This ROC curve can be generated from one set of data with the

same settings with only a varying threshold. An ROC curve cannot be generated from different

Chap

ter 2

.3

50

studies without an exact match of study population and analysis characteristics. To determine

the effect of interstudy differences, we carried out a correlation analysis with parameter D

(Appendix A), the natural logarithm of the odds ratio, which is a measure for how well the test

discriminates between the population with and without a lacunar infarct, or with and without

PCSE. This analytical method is described by Moses et al.11 The resulting summary ROC curve

is not based on individual data, but on sensitivity and specificity of each study separately, and

takes into account the number of patients in each study. The calculations were performed using

a standard spreadsheet.

rotterdam tcD study

Our own data were derived from the Rotterdam TCD study.18 This study was designed to

evaluate the diagnostic and prognostic value of transcranial Doppler ultrasonography in a

prospective cohort of unselected patients with a recent TIA or minor ischemic stroke. Patients

were 18 years and older and had the index event within the preceding 6 months. They were

independent (a score of 3 or less on the modified Rankin scale),16 and the TIA or stroke was

of presumed atherosclerotic origin; this implied that patients with a mechanical heart valve

and a proven dissection were excluded. Patients with atrial fibrillation or a significant symp-

tomatic carotid artery stenosis (>70% stenosis, NASCET criteria) were also excluded. The study

population consisted of patients for whom no other treatment than risk factor modification

and antiplatelet medication was available.

In our study, all patients underwent routine workup including neurological examination,

a CT scan to rule out hemorrhage, and an ECG. These investigations were performed on

admission or first visit to the outpatient clinic, always before the TCD investigation. Risk factors

(diabetes mellitus, smoking, hypertension, increased serum cholesterol level) were assessed. A

duplex-ultrasound scan of the carotid arteries was made in all patients with an anterior circula-

tion stroke. Echocardiography was done in randomly selected patients, but also in patients with

a history of cardiac disease, abnormalities on ECG, or a cardiac bruit on physical examination. To

address the value of TCD in diagnosing stroke subtype, we included only patients with a recent

infarct on the CT scan. To address the value of TCD in diagnosing PCSE, we included all patients

in whom echocardiography was performed.

Our study included patients in the subacute phase of stroke. This differed significantly from

the other studies, which were acute phase studies. We therefore chose not to directly compare

the results of our study to the other studies.


resuLts

We identified twelve studies2-4,10,19-26 that addressed the value of MES in diagnosing stroke

subtype, and twelve studies3,5,10,19-27 that addressed the diagnostic value of MES in screening

for a PCSE. Eleven of these studies were selected for both purposes. Their characteristics, quality

aspects, technical aspects, and results are described in Tables 1-4.

table 1: Characteristics of the selected studies

Author Year TIA (%) Age (years) Sex (% Male) Time- since onset

A: Stroke subtype

Grosset et al. 1994 20 67 (32-96) 60 <48 hrs.

Daffertshofer et al. 1996 26 63.0 ± 13.9 70 <4 weeks

Kaposzta et al. 1999 0 69.6 ± 12.1 52 <72 hrs.

Del Sette et al. 1997 Unknown 69.4 ± 13.9 68 <72 hrs

Koennecke et al. 1997 15 62 ± 14 67 <48 hrs.

Koennecke et al. 1998 26 60.6 ± 14 63 <48 hrs.

Sliwka et al. 1997 Unknown 62.5 (29-90) 65 <1 week †

Lund et al. 2000 12 73.0 ± 11 53 < 72 hrs. ‡

Serena et al. 2000 29 65.1 ± 12.3 74.2 69.5 ± 44 hrs.

Iguchi et al. 2007 0 71.6 54 <24 hrs.

Poppert et al. 2006 Unknown 59.4 64 5.3 ± 3.5 days

Idicula et al. 2010 5 70 ± 15.5 72.5 < 6 hrs.

B: Potential cardiac source of embolism % Mechanical heart valves

Daffertshofer et al. 1996 26 63.0 ± 13.9 70 <4 weeks 0

Kaposzta et al. 1999 0 69.6 ± 12.1 52 <72 hrs. 0

Del Sette et al. 1997 Unknown 69.4 ± 13.9 68 <72 hrs 0

Koennecke et al. 1997 15 62 ± 14 67 <48 hrs. 10

Koennecke et al. 1998 26 60.6 ± 14 62 <48 hrs. 2

Sliwka et al. 1997 Unknown 62.5 (29-90) 65 <1 week † 0

Tong et al. 1995 0 70 ± 14 58 <48 hrs. 7

Lund et al. 2000 12 73.0 ± 11 53 < 72 hrs. ‡ Unknown

Serena et al. 2000 29 65.1 ± 12.3 74.2 69.5 ± 44 hrs. Unknown

Iguchi et al. 2007 0 71.6 54 <24 hrs. 0

Poppert et al. 2006 Unknown 59.4 64 5.3 ± 3.5 days 0

Idicula et al. 2010 5 70 ± 15.5 72.5 < 6 hrs. Unknown

† A second TCD investigation was carried out 24 hrs later, and a third within one week‡ A second TCD investigation was carried out 5 days later

Chap

ter 2

.3

52

tabl

e 2:

Qua

lity

aspe

cts

of th

e re

view

ed s

tudi

es

Auth

orYe

arRe

fere

nce t

est

Spec

trum

repo

rted

Cons

ecut

ive p

atien

tsVe

rifica

tion

rate

(%)

Verifi

catio

n ra

tioBl

ind

asse

ssm

ent o

f TCD

Blin

d as

sess

men

t of r

efer

ence

test?

Win

dow

failu

re re

porte

d

A. St

roke

subt

ype

Gros

set e

t al.

1994

TOAS

TYe

sYe

s10

01

+-

Yes

Daffe

rtsho

fer e

t al.

1996

2 CT’s

Yes

Unkn

own

100

1+

-No

Kapo

szta

et al

.19

99TO

AST

Yes

Yes

100

1+

-Ye

s

Del S

ette

et al

.19

97TO

AST

Yes

Yes

100

1+

-Ye

s

Koen

neck

e et a

l.19

971 C

TYe

sYe

s10

01

+-

Yes

Koen

neck

e et a

l.19

981 C

TYe

sYe

s10

01

+-

Yes

Sliwk

a et a

l.19

971 C

TYe

sUn

know

n10

01

+-

Yes

Lund

et al

.20

00TO

AST

Yes

Yes

100

1+

-Ye

s

Sere

na et

al.

2000

TOAS

TYe

sYe

s10

01

+-

Yes

Iguc

hi et

al.

2007

TOAS

TYe

sYe

s10

01

+-

Yes

Popp

ert e

t al.

2006

TOAS

TYe

sYe

s10

01

++

No

Idicu

la et

al.

2010

TOAS

TYe

sNo

100

1-

-Ye

s

B: Po

tent

ial ca

rdiac

sour

ce o

f em

bolis

m

Daffe

rtsho

fer e

t al.

1996

Ill de

fined

Yes

Unkn

own

100

1+

-No

Kapo

szta

et al

.19

99TO

AST

Yes

Yes

62Un

know

n+

-Ye

s

Del S

ette

et al

.19

97TO

AST

Yes

Yes

100

1+

-Ye

s

Koen

neck

e et a

l.19

97TO

AST

Yes

Yes

76Un

know

n+

-Ye

s

Koen

neck

e et a

l.19

98TO

AST

Yes

Yes

96.6

Unkn

own

+-

Yes

Sliwk

a et a

l.19

97Ill

defin

edYe

sUn

know

n10

01

+-

Yes

Tong

et al

.19

95Ill

defin

edYe

sUn

know

n10

01

+-

No

Lund

et al

.20

00TO

AST

Yes

Yes

44.6

Unkn

own

++

Yes

Sere

na et

al.

2000

Ill de

fined

Yes

Yes

Unkn

own

Unkn

own

+-

Yes

Iguc

hi et

al.

2007

TOAS

TYe

sYe

sUn

know

nUn

know

n+

-Ye

s

Popp

ert e

t al.

2006

TOAS

TYe

sYe

s85

.3Un

know

n+

-No

Idicu

la et

al.

2010

TOAS

TYe

sNo

Unkn

own

Unkn

own

--

Yes


tabl

e 3

Tech

nica

l asp

ects

of t

he M

ES d

etec

tion

met

hod

in e

ach

stud

y.

Auth

orYe

arUl

traso

und

devic

e In

sona

ted

arte

ryDe

pth

Met

hod

Decib

el th

resh

old

Sam

ple v

olum

eFF

T size

FFT o

verla

pHi

gh p

ass fi

lter s

ettin

gRe

cord

ing

time

Gros

set e

t al.

1994

TC 20

00, N

icolet

MCA

46-5

4 mm

A+H†

3 dB

--

--

30

Daffe

rtsho

fer e

t al.

1996

TCD7

/ Mul

tidop

, DW

L M

CA50

-56 m

mH

4 dB

--

--

48 (3

0-60

)

Kapo

szta

et al

.19

99TC

4040

, Nico

let/E

ME

MCA

52±3

.4 m

mH

7 dB

5 mm

128

>66%

-60

Del S

ette

et al

.19

97M

ultid

op X

, DW

LM

CA-

A+H

8 dB

--

--

30

Koen

neck

e et a

l.19

97TC

2020

, EM

E/Ni

colet

PCA

60-7

0 mm

H9 d

B10

-12 m

m12

867

-90%

-20

Koen

neck

e et a

l.19

98TC

2020

, EM

E/Ni

colet

MCA

45-5

8 mm

H9 d

B10

-12 m

m12

825

-81%

-30

Sliwk

a et a

l.19

97M

ultid

op X

, DW

LM

CA-

H3 d

B6 m

m-

--

30

Tong

et al

.19

95M

edas

onics

--

?3 d

B-

--

-30

Lund

et al

.20

00TC

4040

, EM

E/Ni

colet

MCA

49.9±

2.3m

mH

4 dB

10 m

m12

867

%12

0 Hz

45

Sere

na et

al.

2000

Mul

tidop

X, D

WL

MCA

45-6

0 mm

A9 d

B5 m

m12

8-

100 H

z30

Iguc

hi et

al.

2007

Mul

tidop

X, D

WL

Pione

er TC

8080

MCA

50-5

5 mm

H?

--

--

20

Popp

ert e

t al.

2006

Mul

tidop

, DW

LM

CA-

H11

dB

-64

- 256

--

30

Idicu

la et

al.

2010

Pione

er TC

8080

MCA

56 ±

4 m

mA

7dB

10 m

m-

--

60

Rotte

rdam

TCD

Mul

tidop

X, D

WL

MCA

45-6

0 mm

H7 d

B5 m

m12

867

%-

30

† A=A

utom

ated

det

ectio

n pr

ogra

m, H

=Hum

an o

bser

ver

Chap

ter 2

.3

54

tabl

e 4:

Qua

ntita

tive

com

paris

on o

f the

revi

ewed

stu

dies

Auth

orYe

arNu

mbe

r of p

atien

ts Nu

mbe

r of p

atien

ts wi

th a

posit

ive

ref. t

est

Num

ber o

f MES

-pos

itive

pa

tient

sNu

mbe

r of M

ES-p

ositi

ve

patie

nts w

ith re

f. Tes

tSe

nsiti

vity (

=Tru

e Pos

itive

Ra

te)

1-sp

ecifi

city (

=Fals

e Pos

itive

Ra

te)

A. St

roke

subt

ype:

non-

lacun

ar st

roke

Gros

set e

t al.

1994

4133

2929

0.88

0

Daffe

rtsho

fer e

t al.

1996

280

187

2626

0.14

0

Kapo

szta

et al

.19

9910

080

1616

0.20

Del S

ette

et al

.19

9775

209

90.4

50

Koen

neck

e et a

l.19

9728

114

20.1

80.1

2

Koen

neck

e et a

l.19

9810

276

2619

0.25

0.27

Sliwk

a et a

l.19

9778

6940

380.5

50.2

2

Lund

et al

.20

0073

5619

160.2

90.1

8

Sere

na et

al.

2000

182

6417

170.2

70

Iguc

hi et

al.

2007

125

9861

530.5

40.3

0

Popp

ert e

t al.

2006

653

506

3737

0.07

0

Idicu

la et

al.

2010

4038

2525

0.66

0

Rotte

rdam

TCD

2011

120

645

00

0.09


B. Po

tent

ial ca

rdiac

sour

ce o

f em

bolis

m

Daffe

rtsho

fer e

t al.

1996

143

654

40.0

60

Kapo

szta

et al

.19

9980

226

10.0

50.0

9

Del S

ette

et al

.19

9758

234

30.1

30.0

3

Koen

neck

e et a

l.19

9741

208

80.4

0

Koen

neck

e et a

l.19

9810

463

1912

0.19

0.17

Sliwk

a et a

l.19

9744

2019

90.4

50.4

2

Tong

et al

.19

9533

233

30.1

30

Lund

et al

.20

0066

1918

100.5

30.1

7

Sere

na et

al.

2000

143

5411

100.1

90.0

1

Iguc

hi et

al.

2007

105

5334

190.5

60.4

8

Popp

ert e

t al.

2006

550

1714

35

0.03

0.03

Idicu

la et

al.

2010

276

114

0.36

0.125

Rotte

rdam

TCD

2011

149

57

00

0.05

Chap

ter 2

.3

56

characteristics of the studies

The studies were published in the years 1994 through 2010. The studies were similar with

respect to demographic characteristics of the study population, and the timing of the investiga-

tion relative to the onset of symptoms (24 to 72 hours in most, less than 4 weeks in one study).

technical aspects

Four of the 13 studies described the method of intensity measurement of the signal in detail.

Information about the algorithm for MES detection was lacking in most studies. The detection

threshold that was employed in each study varied from 3 to 9 dB.

None of the studies reported all 14 parameters suggested by the International Consensus

Group on Microembolus Detection.8 Most of these parameters influence the intensity of a

microembolic signal and may therefore affect test accuracy. Only five studies reported at least

7 of the 14 parameters, and the remaining five studies reported less than 7. The parameters

reported by all thirteen studies were the insonated artery, the transmitted ultrasound fre-

quency and the length of the recording time. All studies except two reported the depth of the

insonated artery. Six studies reported the size of the sample volume. Only four studies reported

the FFT-overlap. FFT length was never reported. Presumably, all studies used pulsed wave Dop-

pler ultrasound, but only two reported this information. Scale settings were reported in just one

study. In all studies ultrasound frequency was 2 MHz.

Diagnosis of stroke subtype

The sensitivity for non-lacunar stroke ranged from 0.14 to 0.88 and the specificity ranged

from 0.73 to 1.0 (Table 4). In the nine studies with a robust reference test, based on the

TOAST criteria,12 specificity ranged from 0.82 to 1. In these studies, the mean D increased

from 2.41 to 3.33, for a sensitivity of 0.76 and a specificity of 0.90 at the optimal point of the

sROC (Fig.1). Sensitivity increased when TCD investigation was carried out sooner after stroke

onset (Table 1 & 4, Figure 1).

Detection of likely sources of potential cardio-embolism

The sensitivity for PCSE ranged from 0.05 to 0.53 and the specificity from 0.58 to 1.0. The sen-

sitivity in studies that had not included patients with mechanical prosthetic heart valves was

lower than in the other studies. The mean D was 1.40, for a sensitivity of 0.22 and a specificity of

0.94. Since this heterogeneity may be partly caused by the noted differences in definition of the

reference test, we made a distinction between eight studies where a PCSE was defined accord-

ing to the TOAST criteria,12 and the four remaining studies which simply described which kind

of PCSE was observed. After this modification, sensitivity increased to 0.74 in the first group, but

specificity decreased (0.65) at the optimal point on the sROC curve (Fig.2).


0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1

0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1

sens

itivi

ty

1-specificity

Figure 1. Summary ROC curve for diagnosis of stroke subtype. The dotted line in the figure indicates the predefined range of interest, no data are available beyond that line. Nine studies (dots) met our criteria; the summary ROC curve of these studies is the continuous line in the figure. Three studies were excluded (triangels) because in these studies the stroke subtype was based on just the admission CT scan; the summary ROC curve of those studies is the interrupted line in this figure. Results of the present study represented by the asterisk.

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1

0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1

sens

itivi

ty

1-specificity

Figure 2. Summary ROC curve for diagnosis of a potential cardiac source of embolism. The dotted line in the figure indicates the predefined range of interest, no data are available beyond that line. Eight studies (dots) met our criteria; the summary ROC curve of these studies is the continuous line in the figure. Four studies were excluded (triangels) because in these studies the definition of PCSE was incomplete; the summary ROC curve of those studies is the interrupted line in this figure. Results of the present study are represented by the asterisk.

Chap

ter 2

.3

58

characteristics of the rotterdam tcD study

Mean delay between stroke or TIA and TCD examination was 53 ± 49 days (range 1-207). To

address the value of TCD in diagnosing stroke subtype, 120 patients were included, of which 56

had had a lacunar infarction on CT. None of the patients with a non-lacunar infarction had MES

on TCD (Table 4). Thus, sensitivity for stroke subtype was 0, specificity was 0.91.

TO address the value of TCD in diagnosing PCSE, 149 patients were included. Five patients

had a cardiac source of embolism, and five patients had MES, none of which had a PCSE. Sen-

sitivity for PCSE was 0, specificity was 0.95 (Table 4). These data are indicated by the asterisk in

Figure 1 and 2.

Discussion

In this systematic review, we studied the value of MES monitoring in the diagnosis of non-

lacunar infarcts or a PCSE in patients with a recent TIA or minor stroke. We used the summary

ROC curve proposed by Moses et al.11 The comparison of the studies was hampered by the

differences in TCD settings, and by the differences in the criteria for stroke subtype and PCSE

between the studies. However, our results indicate that TCD could be a useful test to distinguish

non-small-vessel disease from small vessel disease. The sensitivity for non-small vessel disease

was 0.76, and specificity was 0.90, in the subgroup of studies that used a robust reference test.

For PCSE, TCD does not seem to be able to adequately distinguish between the presence

and the absence of a PCSE. Sensitivity was low in all studies described in this review. The

sensitivity at the optimal point on the sROC curve in the studies with a robust reference test

was reasonable (0.74), but outside the predefined range of interest. No data were available in

that part of the sROC curve, and therefore any point on the sROC curve outside the range of

interest is not meaningful. Moreover, in two of the five studies with a robust reference test it

was not clear whether patients with mechanical prosthetic heart valves were included or not.

These patients usually have more frequent MES and MES of higher intensity because their MES

probably do not reflect solid particles but cavitation bubbles.28,29 This may therefore influence

the sensitivity and specificity of TCD for the presence of a PCSE.

In the Rotterdam TCD study no patients with a non-lacunar infarction had MES. Moreover,

no patients with a PCSE had MES. The very low frequency of MES in our study could be related

to the relatively long time interval between event and TCD investigation.

Our systematic review provides an estimate of the accuracy of TCD in the diagnosis of PCSE

and ischemic stroke subtype. Data can be viewed in ROC space, and the trade-off between

sensitivity and specificity is made clear.


Limitations

Study populations in this type of analyses are often highly selected, but in our review this is

unlikely: most studies involved consecutive patients, and in most studies the percentage of

PCSE was not abnormally high (range 3 to 70%). Because of the differences in design between

the studies, we cannot determine or quantify the contribution of each separate factor on

diagnostic accuracy.

Only few studies reported a detailed description of the technical aspects of the MES detec-

tion, which were recommended by the International Consensus Committee on Microembolus

Detection. More than half of the studies were published before the publication of the con-

sensus on microembolus detection.8 Reporting all 14 parameters suggested by the Consensus

Committee may lead to redundancy, but the parameters such as ultrasound device, insonated

artery, insonated depth, method of intensity measurement, decibel threshold, sample volume,

FFT size, and FFT overlap have a high face validity. For example, only four studies3,10,19,20 gave a

detailed description of intensity measurement of the ultrasound signal and this varied between

those studies. Since intensity of MES is dependent on the method of intensity measurement,

MES counted in one study might not have reached the decibel threshold in another study.

This is especially important in patients in whom only one or two MES were counted. Moreover,

because of these reported and unreported differences, the employed detection threshold is

not directly comparable between the studies.

Our analysis did not include studies which used TCD and contrast agents to detect a patent

formane ovale, since these studies were mainly different in study design. Direct comparison

of these studies with the selected studies was not possible. Moreover, patent foramen ovale

is a low risk PCSE, and medical and percutaneous treatment options are still under evaluation.

other studies

As far as we know, no systematic review of the diagnostic value of TCD in patients with a TIA

or minor stroke has been carried out. The direct influence of variation in TCD-parameters such

as detection threshold, duration of the investigation, and parameters related to the sampling

method on diagnostic accuracy, could not be analysed on the basis of the reported data. ROC

analysis in a single large study would be the method of choice to assess the effect of changing

the dB threshold for MES detection, and perhaps, the added value of a human observer versus

automated detection.

One other application of TCD in patients with a minor stroke or TIA that has not been stud-

ied sufficiently, is its potential in predicting long term outcome and recurrent strokes. In our

opinion, this has to be studied in a large cohort of patients with adequate follow up. This will

have to be studied with unambiguous criteria that can be duplicated in other TCD laboratories.

Chap

ter 2

.3

60

Final conclusions and clinical relevance

The sensitivity and specificity for PCSE of MES detection with transcranial Doppler ultrasound is

not high enough to recommend its use for screening prior to more invasive diagnostic investi-

gations, such as transesophageal echocardiography.

The sensitivity and specificity for non-lacunar stroke of MES detection with transcranial

Doppler ultrasound in the diagnosis of non-lacunar stroke is of a more acceptable level. Its

high specificity suggests that in patients with a very recent stroke a confident diagnosis of non-

lacunar stroke can be made, when MES are detected with TCD. Even though MES detection

seems to be of limited diagnostic value in determining PCSE, it may be of use alongside other

clinical information in determining stroke subtype in patients with TIAs, where history and

other diagnostic information provides insufficient clues.


reFerences

1. Kappelle LJ, van Latum JC, Koudstaal PJ, van Gijn J. Transient ischaemic attacks and small-vessel disease. Dutch TIA Study Group. Lancet 1991;337:339-41.

2. Grosset DG, Georgiadis D, Abdullah I, Bone I, Lees KR. Doppler emboli signals vary according to stroke subtype. Stroke 1994;25:382-4.

3. Del Sette M, Angeli S, Stara I, Finocchi C, Gandolfo C. Microembolic signals with serial transcranial Doppler monitoring in acute focal ischemic deficit. A local phenomenon? Stroke 1997;28:1311-3.

4. Sliwka U, Lingnau A, Stohlmann WD, Schmidt P, Mull M, Diehl RR, Noth J. Prevalence and time course of microembolic signals in patients with acute stroke. A prospective study. Stroke 1997;28:358-63.

5. Tong DC, Bolger A, Albers GW. Incidence of transcranial Doppler-detected cerebral microemboli in patients referred for echocardiography. Stroke 1994;25:2138-41.

6. Markus HS, Ackerstaff R, Babikian V, Bladin C, Droste D, Grosset D, Levi C, Russell D, Siebler M, Tegeler C. Intercenter agreement in reading Doppler embolic signals. A multicenter international study. Stroke 1997;28:1307-10.

7. Markus HS, Molloy J. Use of a decibel threshold in detecting Doppler embolic signals. Stroke 1997;28:692-5.

8. Ringelstein EB, Droste DW, Babikian VL, Evans DH, Grosset DG, Kaps M, Markus HS, Russell D, Siebler M. Consensus on microembolus detection by TCD. International Consensus Group on Microembolus Detection. Stroke 1998;29:725-9.

9. van Zuilen EV, Mess WH, Jansen C, van der Tweel I, van Gijn J, Ackerstaff RGA. Automatic embolus detection compared with human experts. A Doppler ultrasound study. Stroke 1996;27:1840-3.

10. Kaposzta Z, Young E, Bath PM, Markus HS. Clinical application of asymptomatic embolic signal detec-tion in acute stroke : a prospective study. Stroke 1999;30:1814-8.

11. Moses LE, Shapiro D, Littenberg B. Combining independent studies of a diagnostic test into a summary ROC curve: data-analytic approaches and some additional considerations. Stat Med 1993;12:1293-316.

12. Adams HPJ, Bendixen BH, Kappelle LJ, Biller J, Love BB, Gordon DL, Marsh EE. Classification of subtype of acute ischemic stroke. Definitions for use in a multicenter clinical trial. TOAST. Trial of Org 10172 in Acute Stroke Treatment. Stroke 1993;24:35-41.

13. Reid MC, Lachs MS, Feinstein AR. Use of methodological standards in diagnostic test research. Getting better but still not good. JAMA 1995;274:645-51.

14. Georgiadis D, Grosset DG, Quin RO, Nichol JA, Bone I, Lees KR. Detection of intracranial emboli in patients with carotid disease. Eur J Vasc Surg 1994;8:309-14.

15. Eicke BM, von LJ, Paulus W. Embolus detection in different degrees of carotid disease. Neurol Res 1995;17:181-4.

16. Ries S, Schminke U, Daffertshofer M, Hennerici M. High intensity transient signals (HITS) in patients with carotid artery disease. Eur J Med Res 1996;1:328-30.

17. Valton L, Larrue V, Arrue P, Geraud G, Bes A. Asymptomatic cerebral embolic signals in patients with carotid stenosis. Correlation with appearance of plaque ulceration on angiography. Stroke 1995;26:813-5.

Chap

ter 2

.3

62


19. Koennecke HC, Mast H, Trocio SHJ, Sacco RL, Ma W, Mohr JP, Thompson JL. Frequency and deter-minants of microembolic signals on transcranial Doppler in unselected patients with acute carotid territory ischemia. A prospective study. Cerebrovasc Dis 1998;8:107-12.

20. Koennecke HC, Mast H, Trocio SSJ, Sacco RL, Thompson JL, Mohr JP. Microemboli in patients with vertebrobasilar ischemia: association with vertebrobasilar and cardiac lesions. Stroke 1997;28:593-6.

21. Daffertshofer M, Ries S, Schminke U, Hennerici M. High-intensity transient signals in patients with cerebral ischemia. Stroke 1996;27:1844-9.

22. Lund C, Rygh J, Stensrod B, Sandset PM, Brucher R, Russell D. Cerebral microembolus detection in an unselected acute ischemic stroke population. Cerebrovasc Dis 2000;10:403-8.

23. Serena J, Segura T, Castellanos M, Davalos A. Microembolic Signal Monitoring in Hemispheric Acute Ischaemic Stroke: A Prospective Study. Cerebrovasc Dis 2000;10:278-82.

24. Poppert H, Sadikovic S, Sander K, Wolf O, Sander D. Embolic signals in unselected stroke patients: prevalence and diagnostic benefit. Stroke 2006;37:2039-43.

25. Idicula TT, Naess H, Thomassen L. Microemboli-monitoring during the acute phase of ischemic stroke: is it worth the time? BMC Neurol 2010;10:79.:79.

26. Iguchi Y, Kimura K, Kobayashi K, Ueno Y, Shibazaki K, Inoue T. Microembolic signals at 48 hours after stroke onset contribute to new ischaemia within a week. J Neurol Neurosurg Psychiatry 2008;79:253-9.

27. Sliwka U, Job FP, Wissuwa D, Diehl RR, Flachskampf FA, Hanrath P, Noth J. Occurrence of transcranial Doppler high-intensity transient signals in patients with potential cardiac sources of embolism. A prospective study. Stroke 1995;26:2067-70.

28. Kaps M, Hansen J, Weiher M, Tiffert K, Kayser I, Droste DW. Clinically silent microemboli in patients with artificial prosthetic aortic valves are predominantly gaseous and not solid. Stroke 1997;28:322-5.

29. Georgiadis D, Mackay TG, Kelman AW, Grosset DG, Wheatley DJ, Lees KR. Differentiation between gaseous and formed embolic materials in vivo. Application in prosthetic heart valve patients. Stroke 1994;25:1559-63.

chapter 3.1Prediction of major vascular events in patients

with a recent TIA or ischemic stroke. A comparison of 7 models

A.D. Wijnhoud

L. Maasland

H.F. Lingsma

E.W. Steyerberg

P.J. Koudstaal

D.W.J. Dippel

Stroke. 2010;41:2178-85.

Chap

ter 3

.1

66

AbstrAct

Background: In patients with a recent TIA or minor stroke, prediction of long term risk of major

vascular events is important, but difficult. We aimed to study the external validity of currently

available prediction models.

Methods: We validated predictions from 3 population-based models (Framingham, SCORE and

INDIANA project) and 4 stroke-cohort-based models (SPI-II, Oxford TIA, Dutch TIA study, and

the ABCD2 study) in an independent cohort of patients with a recent TIA or minor stroke.The

validation cohort consisted of 592 patients with a TIA or minor stroke, with a mean follow-up

of 2 years. The primary outcome was the two-year risk of the composite outcome event of non-

fatal stroke, MI or vascular death. We used calibration graphs and c-statistics to evaluate the 7

models.

Results: The two-year risk of the primary outcome event was 12%. Calibration was adequate for

stroke-population based studies. After adjustment for baseline risk and for prevalence of risk

factors, calibration was adequate for the Dutch TIA, the ABCD2, and SPI-II models. Discrimina-

tion ranged from 0.61 to 0.68.

Conclusions: Discrimination was poor for all currently available risk prediction models for

patients with a recent TIA or minor stroke, indicating the need for stronger predictors. Clinical

usefulness may be best for the ABCD2 model which had a limited number of easily obtainable

variables, a reasonable c-statistic (0.64), and good calibration.

Prediction of recurrent stroke and vascular events 67

introDuction

Patients with a recent stroke have an increased long-term risk of new cerebrovascular and

cardiovascular events. Estimates of long term risk of cardiovascular and cerebrovascular events

are important for patients who want to know their individual risk, and for treating physicians,

because in patients with increased long-term risk, more expensive or more hazardous interven-

tions) could be worthwhile. Long term risk seems to be dependent on the uynderlying risk

factors.1

In an American Heart Association (AHA) statement it was pointed out that validated predic-

tion models for long-term cardiovascular risk in patients with ischemic stroke or TIA were not

available.2 The use of a population-based prediction model, i.e. the Framingham risk score,3

was recommended, however, this model has not been evaluated and compared with other

prediction models to predict long-term cerebrovascular and cardiovascular risk in clinical prac-

tice. Treatment recommendations based on predictive models have been published and are

currently used for patients with a significant carotid artery stenosis and for patients with atrial

fibrillation.4,5 For patients without AF or a carotid artery stenosis, more precise risk estimations

are needed.6,7 For this purpose, we need a reliable prognostic model with good discrimination

between patients who will have new events and those who do not.

The aim of the present study is to determine which prediction models are adequate for

long-term risk estimation for cardiovascular or cerebrovascular events in TIA and minor stroke

patients. We primarily focused on major vascular events, i.e. non-fatal stroke, myocardial infarc-

tion and vascular death, because these affect health status most and are the focus of interven-

tion studies. Secondarily, we considered fatal and non-fatal stroke.

Chap

ter 3

.1

68

methoDs

selection of prediction models

We compared the external validity, i.e. calibration and discrimination, of 3 population-based

models (the Framingham risk score for cardiovascular events,3 the Framingham risk score for

stroke,8 SCORE,9 and the INDIANA project cardiovascular risk score10), and 4 stroke-cohort-

based models (SPI-II,11 the Oxford TIA,7 the Dutch TIA study12, and the ABCD2 score13), in an

independent cohort of patients with a recent TIA or minor stroke (Table 1). All models were

designed to predict long term outcomes, except for the ABCD2 score which predicts 90-day

risk of stroke. The stroke-population based models were designed to predict events after TIA

or stroke, the population-based models were designed to predict first ever stroke or cardio-

vascular events. These models were based on well-described large cohorts of patients with TIA

or minor stroke, and had the relative risks of the predictors estimated in a multiple (logistic or

proportional hazards) regression model. The models predicted stroke and other cardiovascular

events.

The Stroke Prognosis Instrument I (SPI-I) was developed in a small cohort of patients with

a recent stroke. Kernan et al created SPI-II by incorporating new predictive variables identified

in a cohort of patients from the WEST study, and validated it in three cohorts of patients from

several secondary prevention trials.11

Hankey et al. developed a prediction equation for recurrent vascular events, based on eight

clinical prognostic factors from a cohort of 469 hospital-referred TIA patients.7 The prediction

model was validated in cohorts of TIA patients from the Oxfordshire Community Stroke Project

and the UK-TIA study.14

The Dutch TIA trial investigators developed a set of predictors of major vascular events and

of stroke. Their prediction model was based on data of patients with a TIA or minor stroke, who

entered a multicenter, randomized controlled clinical trial with a 2x2 factorial design, of high

versus low dose aspirin and propanolol versus placebo.12,15

The ABCD2 score calculates the 2, 7, and 90 day stroke risk in TIA patients.13 This prediction

model was based on TIA patients presenting within 1 day of onset of symptoms. We used the

90-day risk score, since this was closest to the two-year risk calculated in the validation cohort.

The three other models were population based models which have been widely used to

assess cardiovascular risk. For risk of major vascular events we used the Framingham risk score

for cardiovascular events, published in 1998.3 This model is based on categorical variables. For

risk of stroke, we used the Framingham risk score for stroke, published in 1994.8

The SCORE prediction model methodology differs slightly from the other models. Annual,

age and sex-dependent rates of coronary and vascular event were estimated from the data

in an accelerated failure time model (Weibull). This model made use of age as a measure of

exposure time to risk rather than a risk factor. Estimates of mortality rates were based on obser-

vations in age-categories.9


tabl

e 1.

Ove

rvie

w o

f the

sev

en p

redi

ctio

n m

odel

s

Stud

ySP

I-II

Oxfo

rd TI

ADu

tch T

IAAB

CD2

Fram

ingh

amSC

ORE

INDI

ANA

proj

ect

Sour

ce p

opul

atio

nSt

roke

trial

sHo

spita

l coh

ort

Stro

ke R

CTHo

spita

l coh

ort

Popu

latio

n co

hort

Prev

entio

n tri

alsPr

even

tion

trials

Outc

omes

a. St

roke

or d

eath

a. St

roke

, MI o

r vas

cular

dea

thb.

Fata

l or n

on-fa

tal s

troke

c. Co

rona

ry ev

ent

a. St

roke

, MI o

r vas

cular

de

ath

b. Fa

tal o

r non

-fata

l stro

ke

a. St

roke

a. Va

scul

ar ev

ents

(card

iova

scul

ar ri

sk an

d ce

rebr

ovas

cular

risk

se

para

tely)

a. Fa

tal c

oron

ary

hear

t dise

ase

b. Fa

tal v

ascu

lar (n

on-

coro

nary

) dise

ase

a. Fa

tal c

oron

ary h

eart

dise

ase

b. Fa

tal s

troke

c. Fa

tal c

ardi

ovas

cular

dise

ase

Time w

indo

w2 y

ears

5 yea

rs4 y

ears

2, 7,

90 d

ays

10 ye

ars

10 ye

ars

2.0 to

6.9 y

ears

Pred

ictor

s (n)

78

175

95

11

Dem

ogra

phics

Age G

ende

rAg

e Gen

der

Age G

ende

rAg

eAg

e Gen

der

Age G

ende

rAg

e Gen

der

Clin

ical c

hart.

Stro

ke vs

TIA

Amau

rosis

fuga

x onl

y>1

atta

ckre

sidua

l sig

ns

Amau

rosis

fuga

x onl

y>1

atta

ckpe

rsisti

ng>6

wks

dysa

rthria

verti

go

Dura

tion

of

sym

ptom

s Cl

inica

l sym

ptom

s of

TIA

Ri

sk fa

ctor

sPr

ior s

troke

Seve

re h

yper

tens

ion

Hear

t fail

ure

Diab

etes

Mell

itus

Perip

hera

l arte

rial d

iseas

eIsc

hem

ic he

art d

is.Di

abet

es M

ellitu

sAn

gina

pec

toris

Perip

hera

l arte

rial d

iseas

e

Systo

lic B

PDi

abet

esTo

tal C

hol/H

DL-c

hol*

Hype

rtens

ion/

SBP

Diab

etes

Mell

itus

Smok

ing

Atria

l fibr

illatio

n†

CVD†

Tota

l cho

leste

rol

Syst

bloo

d pr

essu

reSm

okin

g

Tota

l cho

leste

rol

Syst

bloo

d pr

essu

reSm

okin

gPr

evio

us m

yoc.

infa

rctio

nPr

evio

us st

roke

Diab

etes

Mell

itus

Im

agin

gBo

rder

zone

infa

rct

Any o

ther

infa

rct

WM

L

Ot

her

Left

vent

ricul

ar h

yper

troph

yLe

ft ve

ntric

ular

hyp

ertro

phy

Incr

term

P wa

veAn

tero

sept

al in

fST

dep

ress

ion

Left

vent

ricul

ar h

yper

troph

y‡Le

ft ve

ntric

ular

hyp

ertro

phy

Antih

yper

tens

ive tr

eatm

ent

Seru

m cr

eatin

in

* ca

rdio

vasc

ular

risk

onl

y† c

ereb

rova

scul

ar ri

sk o

nly

Chap

ter 3

.1

70

Pocock et al. published a prediction instrument based on data from 8 randomized controlled

trials of antihypertensive treatment in asymptomatic individuals, the INDIANA project. They

developed three separate models for overall cardiovascular mortality, fatal coronary heart

disease and fatal stroke.10

Validation cohort

The validation cohort consisted of 592 consecutive patients included in the Rotterdam Transcra-

nial Doppler study.16 Patients were recruited in our hospital. This study was designed to evaluate

the diagnostic and prognostic value of transcranial Doppler ultrasonography in patients with a

recent TIA or minor ischemic stroke. Patients were 18 years and older and had the index event

within the preceding 6 months. They were independent (a score of 3 or less on the modified

Rankin scale),17 and the TIA or stroke was of presumed atherosclerotic origin; this implied that

patients with a mechanical heart valve and a proven dissection were excluded. Patients with

atrial fibrillation or a significant symptomatic carotid artery stenosis (>70% stenosis, NASCET

criteria) were also excluded. Follow-up started at time of recruitment. The mean time between

index event and recruitment was 51 ± 45 days. The mean follow-up in this study was 755 days

or 2.1 years (interquartile range 0.9 to 3.1). The study population consisted of patients for whom

no other treatment than risk factor modification and antiplatelet medication was available.

Procedure and definitions

The primary outcome was the composite end point of stroke, myocardial infarction and vascu-

lar death. The secondary outcome was the composite end point of fatal or non-fatal stroke. In

the validation cohort, stroke was defined as a focal neurological deficit, resulting in disability for

more than 24 hours, confirmed by a neurologist, with CT scan, if possible.

Myocardial infarction was defined as an episode of precordial chest pain accompanied by

ECG evidence of recent infarction, and/or release of cardiac enzymes. Vascular death was death

within 4 weeks after stroke or MI, or sudden death. Follow-up was done annually by telephone

survey by an experienced nurse. If patients reported any hospital visits or any symptoms sug-

gesting a vascular event, their treating physician was contacted for further information or dis-

charge letters. In the validation cohort Kaplan-Meier analysis of survival was used to estimate

the two-year risk of the primary and secondary outcome.

The validation procedure was similar for each prediction model. First we estimated the

actual two-year risk of primary and secondary outcome events for each patient in the validation

cohort using Kaplan-Meier survival analysis. For missing values, the mean value of a variable

was imputed. We then calculated the two-year risk as predicted by the seven models. To do

so we used the original prediction equations of each model. Each equation was adjusted for

the mean overall risk and for the prevalence of risk factors in the validation cohort, as recom-

mended by several authors.18,19


calibration and discrimination

Two aspects of validity were examined: calibration and discrimination. Calibration, or reliability,

measures how closely predicted outcomes agree with actual outcomes. Discrimination refers

to the ability to distinguish patients with different outcomes.20 The predicted probabilities of

vascular events should be trustworthy (calibration) and extreme (discrimination).

Calibration-in–the-large reflects whether the overall outcome of the study cohort was close

to the average predicted two-year risk from a model. We constructed calibration plots, in which

observed two-year outcome was plotted against predicted two-year risk (using a Kaplan-Meier

survival curve). We indicate outcome by quintiles of predicted probabilities. Calibration curves

can be approximated by a regression line (or calibration line) with intercept (α) and slope (β).

Well-calibrated models have α=0 and β=1. We calculated slopes for each prediction model.

Discrimination was quantified with the concordance (c)-statistic.The c-statistic resembles the

area under the ROC curve. A c-statistic of 1 implies a test with perfect sensitivity and specificity,

while a value of 0.5 implies that the model predictions are no better than chance.20

resuLts

comparability of the cohorts

We first compared the distribution of prognostic factors in the seven derivation cohorts

(Table 2). People in the population-based studies from the INDIANA project and Framingham

were younger than patients in the stroke cohorts and by definition did not have a history of

stroke or myocardial infarction. For the SCORE population, the mean age or age distribution

was not stated. In this study, relatively young subjects had participated, and subjects aged

40 to 60 were particularly well represented. In the Oxford TIA cohort, all patients had a TIA,

and about one third had amaurosis fugax (Table 2). In the validation cohort 57 major vascular

events occurred during follow-up, for a two-year risk of 12 %, and 41 fatal or non-fatal strokes,

for a two year-risk of 9%.

Table 4 shows the observed the predicted two-year risk of stroke, myocardial infarction or

vascular death, as well as fatal or non-fatal stroke. The SPI-II overestimated the risk for both out-

come events in patients with low risk and underestimated in patients with high risk, whereas

Oxford TIA, the Dutch TIA trial, and ABCD2 score overestimated the risk for both outcome

events (Figure 1).

Discrimination

Discrimination varied between 0.61 and 0.68 for the risk of stroke, myocardial infarction or

vascular death, and between 0.58 and 0.65 for the risk of fatal or non-fatal stroke (Table 4).

Discrimination was higher in the stroke-cohort-based studies than in the population-based

studies, but remained below 0.70.

Chap

ter 3

.1

72

table 2. Baseline characteristics of the seven prediction model cohorts and the validation cohort. Mean values are given, unless indicated otherwise. - indicates data not available; n.a. indicates not applicable.

Validation cohort

SPI-II Oxford TIA

Dutch TIA

ABCD2 Framing-ham

SCORE INDIANA project

N in study 592 525 469 3127 4809 5345 205178 47008

Age (years) 62 - 62 65 70 49 - 55

Age over 60 - - - - 77% - - -

Age over 65 44% 73% - 53% - - -

Age over 70 29% 57% 25% 34% - 5% -

Male sex 60% 0% 68% 65% 47% 47% 57% 57%


TIA (not stroke) 54% 23% 100% 32% 100% n.a. n.a. n.a.

Multiple attacks 20% - - 32% - n.a. n.a. n.a.

Amaurosis fugax only 6% - 34% 6% - n.a. n.a. n.a.

Risk factors

Previous stroke 21% 20% 0% 0% - 0% n.a. 1%

Previous MI1 24% 24% 21% 10% - 0% n.a. 5%

Diabetes mellitus 11% 31% 5% 8% 17% 4.6% - 3%

Angina pectoris 9% 6% - 9% - 0%

Current smoker 26% - 47% 44% - 39% 40%

Total chol. (mmol/l) 5.7 - 6.7 - - 5.4 6.1

LDL-chol. (mmol/l) 3.8 - - - - 3.5 - -

HDL-chol. (mmol/l) 1.3 - - - - 1.3 1.4 -

SBP (mmHg) 148 -2 - 158 - 1463 133 162

DBP (mmHg) 86 - - 91 - 82 - -

SBP > 140 mm Hg - - - - 69% - - -

DBP > 90 mm Hg - - - - 30% - - -

BMI (kg/m2) 26.2 - - - - 25.8 - -

* Any MI, by history or ECG.† Severe hypertension (systolic BP>180 or diastolic BP>100 mHg) in 31 patients (6%).‡ Median systolic and diastolic BP instead of means were reported in the Framingham study


table 3: Estimated two-year risk in the validation and derivation cohorts*

Validation cohort

SPI-II Oxford TIA

Dutch TIA

ABCD2 * Framingham SCORE INDIANAproject

Stroke 9% - 9% 7% 7% 0.5% - † -

Stroke or death 13% 20% - - 9% 3% - † -

MI 4% - 6% - - 3% 3.5%‡ 0.5%

Stroke, MI or vasc death 12% - 14% 12% - 3% 5.7%

* estimated 90-day risk in the ABCD2 study† Product limit estimates were available for all studies but SCORE.‡ Cumulative risk at age 65

table 4. Calibration and discrimination of the seven prediction models.A . Major vascular events

Calibration Discrimination*

Predicted two-year risk

Observed two-year risk Slope [95% CI] c-statistic [95% CI]

SPI-II 13 % 12 % 1.62 [ 0.57 – 2.66] 0.68 [ 0.61 - 0.75 ]

Oxford TIA 17 % 12 % 0.60 [ 0.32 – 0.88] 0.66 [ 0.58 - 0.74 ]

Dutch TIA 14 % 12 % 0.92 [-0.27 – 2.11] 0.64 [ 0.56 - 0.72 ]

ABCD2 14% 12% 0.68 [ 0.40 – 0.96] 0.64 [ 0.57 - 0.70 ]

Framingham 14 % 12 % 0.37 [-0.46 – 1.21] 0.64 [ 0.57 - 0.72 ]

SCORE 12 % 12 % 0.34 [-0.29 – 0.97] 0.61 [ 0.53 - 0.69 ]

INDIANA project 21 % 12 % 0.21 [-0.22 – 0.63] 0.61 [ 0.54 - 0.69 ]

* The nullhypothesis that all values were equal was rejected (p=0.02, χ2 =15,27, 6 d.f.)

b . For stroke

Calibration Discrimination*

Predicted two-year risk

Observed two-year risk Slope [95% CI] c-statistic [95% CI]

SPI-II 10 % 9 % 1.12 [ 0.24 – 1.99] 0.64 [ 0.56 - 0.72 ]

Oxford TIA 13 % 9 % 0.47 [ 0.22 – 0.72] 0.63 [ 0.54 - 0.72 ]

Dutch TIA 11 % 9 % 0.56 [ 0.13 – 0.99] 0.64 [ 0.57 - 0.72 ]

ABCD2 11 % 9 % 0.58 [ 0.09 – 1.07] 0.61 [ 0.53 – 0.69 ]

Framingham 10 % 9 % 0.44 [-0.08 – 0.97] 0.58 [ 0.50 - 0.68 ]

SCORE 9 % 9 % 0.25 [-0.21 – 0.71] 0.58 [ 0.49 - 0.68 ]

INDIANA project 16 % 9 % 0.19 [-0.02 – 0.39] 0.61 [ 0.52 - 0.69 ]

* The 0 hypothesis that all areas were equal was not rejected (p=0.55, χ2 =4.93, 6 d.f.)

Chap

ter 3

.1

74

0,3

0,4

0,5

0,6

Obs

erve

d pr

opor

tion

of m

ajor

vas

cula

r eve

nts

SPI-II

0

0,1

0,2

0 0,1 0,2 0,3 0,4 0,5 0,6

Obs

erve

d pr

opor

tion

of m

ajor

vas

cula

r eve

nts

Estimated probability of major vascular events

0,3

0,4

0,5

0,6

Obs

erve

d pr

opor

tion

of m

ajor

vas

cula

r eve

nts

UK TIA trial

0

0,1

0,2

0 0,1 0,2 0,3 0,4 0,5 0,6

Obs

erve

d pr

opor

tion

of m

ajor

vas

cula

r eve

nts


0,3

0,4

0,5

0,6

Obs

erve

d pr

opor

tion

of m

ajor

vas

cula

r eve

nts

Dutch TIA trial

0

0,1

0,2

0 0,1 0,2 0,3 0,4 0,5 0,6

Obs

erve

d pr

opor

tion

of m

ajor

vas

cula

r eve

nts


0,3

0,4

0,5

0,6

Obs

erve

d pr

opor

tion

of m

ajor

vas

cula

r eve

nts

ABCD2

0

0,1

0,2

0 0,1 0,2 0,3 0,4 0,5 0,6

Obs

erve

d pr

opor

tion

of m

ajor

vas

cula

r eve

nts


0,3

0,4

0,5

0,6

Obs

erve

d pr

opor

tion

of m

ajor

vas

cula

r eve

nts

Framingham

0

0,1

0,2

0 0,1 0,2 0,3 0,4 0,5 0,6

Obs

erve

d pr

opor

tion

of m

ajor

vas

cula

r eve

nts


0,3

0,4

0,5

0,6

Obs

erve

d pr

opor

tion

of m

ajor

vas

cula

r eve

nts

SCORE

0

0,1

0,2

0 0,1 0,2 0,3 0,4 0,5 0,6

Obs

erve

d pr

opor

tion

of m

ajor

vas

cula

r eve

nts


0,3

0,4

0,5

0,6

Obs

erve

d pr

opor

tion

of m

ajor

vas

cula

r eve

nts

Indiana Project

0

0,1

0,2

0 0,1 0,2 0,3 0,4 0,5 0,6

Obs

erve

d pr

opor

tion

of m

ajor

vas

cula

r eve

nts


(A)


0,3

0,4

0,5

0,6

Obs

erve

d pr

opor

tion

of s

trok

e

SPI-II

0

0,1

0,2

0 0,1 0,2 0,3 0,4 0,5 0,6

Obs

erve

d pr

opor

tion

of s

trok

e

Estimated probability of stroke

0,3

0,4

0,5

0,6

Obs

erve

d pr

opor

tion

of st

roke

UK TIA

0

0,1

0,2

0 0,1 0,2 0,3 0,4 0,5 0,6

Obs

erve

d pr

opor

tion

of st

roke


0,3

0,4

0,5

0,6

Obs

erve

d pr

opor

tion

of st

roke

Dutch TIA

0

0,1

0,2

0 0,1 0,2 0,3 0,4 0,5 0,6

Obs

erve

d pr

opor

tion

of st

roke


0,2

0,3

0,4

0,5

0,6

Obs

erve

d pr

opor

tion

of st

roke

ABCD2

0

0,1

0,2

0 0,1 0,2 0,3 0,4 0,5 0,6

Obs

erve

d pr

opor

tion

of st

roke


0,3

0,4

0,5

0,6

Obs

erve

d pr

opor

tion

of st

roke

Framingham

0

0,1

0,2

0 0,1 0,2 0,3 0,4 0,5 0,6

Obs

erve

d pr

opor

tion

of st

roke


0,2

0,3

0,4

0,5

0,6

Obs

erve

d pr

opor

tion

of st

roke

SCORE

0

0,1

0,2

0 0,1 0,2 0,3 0,4 0,5 0,6

Obs

erve

d pr

opor

tion

of st

roke


0,2

0,3

0,4

0,5

0,6

Obs

erve

d pr

opor

tion

of st

roke

Indiana project

0

0,1

0,2

0 0,1 0,2 0,3 0,4 0,5 0,6

Obs

erve

d pr

opor

tion

of st

roke


(b)Figure 1. Calibration graph. Mean predicted probabilities versus observed frequencies of the composite outcome event of A. non-fatal stroke, non-fatal myocardial infarction or vascular death, and B. Stroke (in quintiles).

Chap

ter 3

.1

76

Discussion

This is the first study comparing the external validity of long term prediction models. In a scien-

tific statement for healthcare professionals from the Stroke Council and the Council on Clinical

Cardiology of the American Heart Association/American Stroke Association, the Framingham

study3 was recommended for long term cardiovascular risk in patients with a TIA or ischemic

stroke.2 The purpose of our study was to find out whether stroke-cohort based studies indeed

perform better and should be used in the future to estimate long term risk of major vascular

events in patients with a TIA or ischemic stroke.

Calibration was fairly good in most models, but in the SPI-II study, the Dutch TIA study, and

the ABCD2 study calibration was best. All models were adjusted for baseline risk and prevalence

of risk factors as suggested by several authors.18,19 Without these adjustments calibration was

poor. Overall, stroke-based prediction models from the Dutch TIA trial, the SPI-II study, and the

ABCD2 study showed best calibration and discrimination. A clinically useful prediction model

shows good calibration, discrimination and uses a limited number of clear-cut, easily available

variables.

The ABCD2 score and the SCORE prediction model used the smallest number of variables in

their prediction rule for long term cardiovascular risk, 5 and 6 respectively, and risk estimation

derived from these studies is therefore easy to obtain. The Framingham prediction model for

cerebrovascular risk included 8 factors, which are all easy to obtain except for left ventricular

hypertrophy for which an ECG is needed. The Dutch TIA study used 17 variables in the predic-

tion rule. The Oxford TIA prediction rule and the INDIANA project prediction rule included ECG

variables, which are more difficult to ascertain. The Dutch TIA prediction rule used ECG variables

that require some expertise, such as left ventricular hyperthrophy by the Casale criteria,21 and

anteroseptal infarction (Table 1), and included also CT scan variables. This makes these models

less attractive to use.

Limitations of the study

Some limitations of this study have to be discussed. First, although the validation cohort was

of reasonable size (592 patients), the effective sample size was not large, with 57 major events,

and 41 fatal or non-fatal strokes. Second, predictions from all models, except for the ABCD2

study, exceeded the two- year risk observed in our validation cohort. We have overcome this

miscalibration by adjusting for this difference in follow-up in our analysis.

We excluded patients with AF or a severe carotid artery stenosis, and focussed on patients with

TIA or minor ischemic stroke. This reduces the heterogeneity of the validation cohort, and may

reduce the discriminatory ability of the models. Risk estimates are more readily available for

carotid artery stenosis as well as for patients with AF. For the remaining group of patients with

TIA or minor stroke there is a particular need for a prediction model.


In the validation cohort as well as in two of the four stroke cohorts, the mean age was rather

low (Table 2). These cohorts consisted of a hospital population. Hospital populations tend to be

of lower age. They may therefore not be representative of patients with TIAs and minor strokes

in the community.

The time between index event and recruitment in the validation cohort was 51 days, which

differs substantially from the ABCD2 study, not the remaining stroke-based population studies.

We have overcome this problem by adjusting for the baseline risk in all validation studies. In

this way, we adjusted for the low number of outcome events compared to the ABCD2 study.

Validity

Although this was a study on long term risk, we also included the ABCD2 model, which was

developed for estimation of short term risk. Calibration and discrimination in the ABCD2 study,

however, did not differ substantially from the long term prediction models. Comparisons with

other studies cannot be made, because similar studies of long term risk assessment in patients

with TIA or ischemic are not available.

Possible improvements

The seven models used dichotomized variables instead of continuous variables. Perhaps with

continuous variables estimations of risk would have been more precise and discrimination may

improve.22 Furthermore, the stroke based prediction models were derived from trial popula-

tions with certain in- and exclusion criteria. The best fitting model for everyday practice will

probably be derived from a representative cohort; this means a consecutive stroke population

without exclusion criteria.

conclusion

Current prediction models for long term prognosis in TIA and stroke patients have limited valid-

ity. Calibration seems to be adequate for most models, but especially discrimination between

high risk patients and low risk patients is relatively poor. Improvements such as implementation

of continuous variables are needed, as well as extension with stronger predictors of outcome.

For now, the SPI-II and the ABCD2 prediction models seem to be most adequate. Of these two,

the ABCD2 may be preferred because of its easy applicability in clinical practice.

Chap

ter 3

.1

78

reFerences

1. Pendlebury ST, Rothwell PM. Risk of recurrent stroke, other vascular events and dementia after tran-sient ischaemic attack and stroke. Cerebrovasc Dis 2009;27 Suppl 3:1-11.:1-11.

2. Adams RJ, Chimowitz MI, Alpert JS, Awad IA, Cerqueria MD, Fayad P, Taubert KA. Coronary risk evalu-ation in patients with transient ischemic attack and ischemic stroke: a scientific statement for health-care professionals from the Stroke Council and the Council on Clinical Cardiology of the American Heart Association/American Stroke Association. Circulation 2003;108:1278-90.

3. Wilson PW, D’Agostino RB, Levy D, Belanger AM, Silbershatz H, Kannel WB. Prediction of coronary heart disease using risk factor categories. Circulation 1998;97:1837-47.

4. Rothwell PM. Medical and surgical management of symptomatic carotid stenosis. Int J Stroke 2006;1:140-9.

5. van WC, Hart RG, Wells GA, Petersen P, Koudstaal PJ, Gullov AL, Hellemons BS, Koefed BG, Laupacis A. A clinical prediction rule to identify patients with atrial fibrillation and a low risk for stroke while taking aspirin. Arch Intern Med 2003;163:936-43.


7. Hankey GJ, Slattery JM, Warlow CP. Transient ischaemic attacks: which patients are at high (and low) risk of serious vascular events? J Neurol Neurosurg Psychiatry 1992;55:640-52.

8. D’Agostino RB, Wolf PA, Belanger AJ, Kannel WB. Stroke risk profile: adjustment for antihypertensive medication. The Framingham Study. Stroke 1994;25:40-3.

9. Conroy RM, Pyorala K, Fitzgerald AP, Sans S, Menotti A, De Backer G, De Bacquer D, Ducimetiere P, Jousilahti P, Keil U, Njolstad I, Oganov RG, Thomsen T, Tunstall-Pedoe H, Tverdal A, Wedel H, Whincup P, Wilhelmsen L, Graham IM. Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. Eur Heart J 2003;24:987-1003.

10. Pocock SJ, McCormack V, Gueyffier F, Boutitie F, Fagard RH, Boissel JP. A score for predicting risk of death from cardiovascular disease in adults with raised blood pressure, based on individual patient data from randomised controlled trials. BMJ 2001;323:75-81.

11. Kernan WN, Viscoli CM, Brass LM, Makuch RW, Sarrel PM, Roberts RS, Gent M, Rothwell P, Sacco RL, Liu RC, Boden-Albala B, Horwitz RI. The stroke prognosis instrument II (SPI-II) : A clinical prediction instru-ment for patients with transient ischemia and nondisabling ischemic stroke. Stroke 2000;31:456-62.

12. The Dutch TIA Trial Study Group. Predictors of major vascular events in patients with a transient ischemic attack or nondisabling stroke. Stroke 1993;24:527-31.

13. Johnston SC, Rothwell PM, Nguyen-Huynh MN, Giles MF, Elkins JS, Bernstein AL, Sidney S. Validation and refinement of scores to predict very early stroke risk after transient ischaemic attack. Lancet 2007;369:283-92.

14. Hankey GJ, Slattery JM, Warlow CP. Can the long term outcome of individual patients with transient ischaemic attacks be predicted accurately? J Neurol Neurosurg Psychiatry 1993;56:752-9.

15. The Dutch TIA Trial Study Group. A comparison of two doses of aspirin (30 mg vs. 283 mg a day) in patients after a transient ischemic attack or minor ischemic stroke. N Engl J Med 1991;325:1261-6.




18. Steyerberg EW, Bleeker SE, Moll HA, Grobbee DE, Moons KG. Internal and external validation of predic-tive models: a simulation study of bias and precision in small samples. J Clin Epidemiol 2003;56:441-7.

19. D’Agostino RB, Sr., Grundy S, Sullivan LM, Wilson P. Validation of the Framingham coronary heart disease prediction scores: results of a multiple ethnic groups investigation. JAMA 2001;286:180-7.


21. Casale PN, Devereux RB, Alonso DR, Campo E, Kligfield P. Improved sex-specific criteria of left ven-tricular hypertrophy for clinical and computer interpretation of electrocardiograms: validation with autopsy findings. Circulation 1987;75:565-72.

22. Royston P, Altman DG, Sauerbrei W. Dichotomizing continuous predictors in multiple regression: a bad idea. Stat Med 2006;25:127-41.

chapter 3.2The prognostic value of pulsatility index, flow

velocity, and their ratio, measured with TCD ultrasound, in patients with a recent TIA or

ischemic stroke.

A.D. Wijnhoud

P.J. Koudstaal

D.W.J. Dippel

Acta Neurol Scand. 2011;124:238-44

Chap

ter 3

.2

82

AbstrAct

Background: Increased flow velocities, and combinations of low mean flow velocity (MFV) and

a high pulsatility index (PI) are associated with intracranial arterial disease. We investigated the

association of MFV and the ratio of PI and MFV (PI-MFV ratio) in the middle cerebral artery with

recurrence of vascular events in patients with a TIA or minor ischemic stroke.

Methods: 598 consecutive patients underwent TCD-investigation. Outcome events were fatal

or non-fatal stroke, and the composite of stroke, myocardial infarction or vascular death (major

vascular events). Hazard ratio’s (HR) were estimated with Cox proportional hazards multiple

regression method, adjusted for age, gender and vascular risk factors.

Results: TCD registration was successful in 489 patients. Mean follow-up was 2.1 years. Cumula-

tive incidence was 9% for all stroke, and 12% for major vascular events. MFV over 60.5 cm/s

increased the risk both for stroke (HR 2.8; 95%CI: 1.3-6.0) and major vascular events (HR 2.6;

95%CI: 1.3-5.0). Each unit increase in PI-MFV ratio was associated with a HR 2.8 (95%CI: 1.7-4.8)

for stroke and HR 2.2 (95%CI: 1.3-3.6) for major vascular events.

Conclusion: In patients with a TIA or non-disabling ischemic stroke, MFV and the PI-MFV ratio

in the middle cerebral artery are independent prognostic factors for recurrent vascular events.

Prognostic value of TCD after TIA or minor stroke 83

introDuction

Transcranial Doppler ultrasound investigation of the intracranial arteries in patients with a

recent stroke or TIA may provide prognostic information in addition to conventional vascular

risk factors. Increased flow velocities in the middle cerebral artery (MCA) may indicate a local

stenosis.1 Furthermore, increased flow velocities in the MCA have been shown to be strongly

related to vascular risk factors: flow velocities increase with hypertension, hypercholesterol-

emia, and in patients with diabetes mellitus.2 This suggests that increased flow velocities may

be related to extra- and intracranial vascular disease. On the other hand, the combination of

low mean flow velocity (MFV) and a high pulsatility index (PI) has been associated with diffuse

stenosis of intracranial arteries in patients with stroke.3 Flow velocities however, decrease with

increasing age and male gender.4,5 Because of these associations, unadjusted flow-velocities

are difficult to interpret. We analysed the prognostic value of TCD- flow-parameters for recur-

rent stroke and other vascular events in a consecutive cohort of patients with a recent TIA or

minor stroke.

methoDs

Patients

We studied patients from a prospective cohort study that investigated the diagnostic and

prognostic value of TCD in patients with a recent TIA or ischemic non-disabling stroke.[2] In

brief, inclusion criteria were a recent (<6 months) TIA or non-disabling ischemic stroke of pre-

sumed arterial origin. Patients had to be over 18 years of age, and had to give informed consent.

Patients had to be independent in most activities of daily living, corresponding with grade 3 or

better on the modified Rankin scale.6,7 We excluded patients with planned carotid surgery or

stenting, because both TCD parameters and risk of recurrent events would be affected by the

treatment. We also excluded patients with mechanical heart valves.

The study was approved by the Medical Ethics Committee and Review Board of the Erasmus

MC in Rotterdam, the Netherlands.

tcD recordings

All patients underwent TCD examination (Multidop X-4, DWL, Sipplingen, Germany). All TCD

recordings were carried out by one investigator (A.W.). TCD examination was performed within

6 months after TIA or non-disabling ischemic stroke. In all patients, peak systolic flow velocity

(PSV) and end-diastolic flow velocity (EDV) was measured with a handheld 2 MHz probe in both

middle cerebral arteries (MCA). Mean flow velocity (MFV) was calculated as EDV + 1/3(PSV-EDV).

The pulsatility index (PI) was calculated as (PSV-EDV)/MFV. Because of the expected interaction

between PI and MFV, we created a new parameter the PI-MFV ratio, calculated as 100xPI/MFV.

Chap

ter 3

.2

84

In a note we added that the multpiplication by 100 is just for practical reasons. The mean of

the above mentioned TCD parameters was calculated as the mean of both left and right sided

measurements. In case of unilateral window failure, the contralateral parameter was taken as

the mean.

Blood pressure was measured automatically with a self-inflating cuff (Dynamap, Datascope,

The Netherlands) during TCD investigation. Pulse pressure was calculated as systolic blood

pressure minus diastolic pressure.



out hemorrhage, and an ECG. These investigations were performed on admission or first visit to

the outpatient clinic, always before the TCD investigation. Risk factors (diabetes mellitus, smok-

ing, hypertension, increased serum cholesterol level) were assessed as described previously.2

A duplex-ultrasound scan of the carotid arteries was made in all patients with an anterior

circulation stroke. Echocardiography was done in patients with a history of cardiac disease,

abnormalities on ECG, or a cardiac bruit on physical examination.

outcome

Primary outcome event was all stroke, both fatal and non-fatal. Secondary outcome event

was the composite of either non-fatal stroke, non-fatal myocardial infarction and death from

all vascular causes, whichever occurred first. Tertiary outcome events were fatal or non-fatal

ischemic stroke, or TIA. The definition of death from vascular causes included sudden death

(unexpected death ocurring within one hour after onset of symptoms, or within 24 hours given

circumstantial evidence) or death from stroke, ischemic heart disease, or peripheral vascular

disease.

Follow-up was done annually by telephone survey by an experienced nurse. If patients

reported any hospital visits or any symptoms suggesting a vascular event, their treating

physician was contacted for further information or discharge letters. All outcome events were

anonimized and next adjudicated by an experienced panel (A.W. and D.D.) without knowledge

of the TCD findings.


The cumulative probability of all outcome events was estimated with Kaplan-Meier survival

analysis. The prognostic value of flow velocity parameters was analysed with Cox proportional

hazards regression, and expressed as a hazard ratio (HR). Quintiles of TCD flow-parameters were

used, because of non-normal distributions, and the lowest quintile was set als reference. For

exploration of the relationship between the outcome events and the TCD flow velocity param-

eters, we used the upper quintiles of the TCD flow velocity parameters. Since PI-MFV ratio is

an interaction factor it was analysed in a model including MFV and PI. In a note we added that


the multiplication by 100 is just for practical reasons. For exploration of the interaction factor

PI-MFV ratio we included the variables MFV, PI, and PI-MFV ratio in the proportional hazards

multipe regression model. Further adjustments for other vascular risk factors were also made

with this method.

resuLts

clinical characteristics

We included 598 consecutive patients in our study. In 4 patients, the diagnosis was revised

shortly after inclusion (1 patient had multiple sclerosis, 2 had focal epileptic seizures and 1 had

migraine with aura). In 105 of the remaining 594 patients (17.7%), we failed to obtain adequate

Doppler data due to two-sided window failure or other limitations.8 Therefore 489 patients

were included in the present analysis. Mean age was 60 years, and two-thirds of the patients

were men. Approximately half of the patients had transient symptoms; more than 75% had

focal ischemia in the anterior circulation. Almost one third of the patients were current smokers,

nearly half had hypertension and almost one sixth had diabetes mellitus (Table 1).

results of tcD examination

Mean time between TIA or stroke and TCD examination was 51 ± 45 days (range 1-207). In 22%

of the patients TCD was performed within 2 weeks. Insonation depth varied from 48 to 56 mm.

Mean MFV was 51.1 ± 14.4 cm/sec, mean PSV was 83.8 ± 22.1 cm/s, and mean EDV was 34.7 ±

12.1 cm/s. Only four patients had a PSV higher than 155 cm/s, only one had a PSV higher than

220 cm/s (223 cm/s).

The PI was 0.93 (SD 0.22). Mean PI-MFV ratio was 2.02 (SD 0.95). Nearly 25% of the patients

had one-sided or double-sided window failure. Patients with window failure were older (71

± 10 vs. 60 ± 13, p<0.001), were more often female (31% vs. 9%, p<0.001), and smoked less

often (9% vs. 31%, p<0.001) than patients without window failure. MFV was lower in men, and

MFV was negatively related to age, whereas diabetes and total serum cholesterol was positively

related to MFV in this study, as described in a previous study of the same study population.2

MFV was linearly related to PI, for every 10 cm/s increase in MFV, PI decreased with 0.05.

outcome events

Mean follow-up was two years and one month (range 17 days to 5.7 years). A recurrent TIA

or stroke occurred in 64 patients. A major vascular event (stroke, myocardial infarction and

vascular death) occurred in 60 patients (Table 2). The cumulative incidence was 9% (95% CI: 7

to 12%) for fatal or non-fatal stroke, 12% (95% CI: 9 to 15%) for stroke, myocardial infarction or

vascular death, and 14% (95% CI: 11 to 17%) for TIA, fatal or non-fatal ischemic stroke.

Chap

ter 3

.2

86

table 1: Baseline patient characteristics.

Overall N=489

MFV£60.5cm/s N=393

MFV>60.5cm/s N=96

Demographics

Age, years (mean ± SD) 60 ± 13 62 ± 12 52 ± 13 p<0.0001

Male gender 323 (66%) 278 (71%) 45 (47%) p<0.0001

Caucasian race 410 (87%) 332 (87%) 78 (85%) NS


TIA 261 (53%) 206 (52%) 55 (57%) NS

Anterior circulation 391 (80%) 318 (81%) 73 (76%) NS

Lacunar syndrome 180 (37%) 152 (39%) 28 (29%) P=0.083

CT characteristics

Any infarct on CT scan 225 (46%) 190 (48%) 35 (36%) P=0.036

White matter lesions on CT scan 62 (13%) 57 (15%) 5 (5%) P=0.014

Risk factors

Smoking, current 140 (29%) 107 (27%) 33 (34%) NS

Hypertension 259 (53%) 216 (55%) 43 (45%) P=0.073

Diabetes 77 (16%) 58 (15%) 19 (20%) NS


Previous myocardial infarction 53 (11%) 45 (12%) 8 (8%) NS

Carotid artery stenosis (≥70%) 37 (8%) 29 (7%) 8 (8%) NS

Body-mass-index, kg/m2 (mean ± SD) 26.1 ± 3.9 26.2 ± 3.8 25.9 ± 4.3 NS

Use of cholesterol lowering medication 123 (26%) 102 (27%) 21 (23%) NS

Cholesterol (mean ± SD)

Total cholesterol,mmol/l 5.7 ± 1.2 5.6 ± 1.1 6.1 ± 1.3 p<0.0001

HDL-cholesterol, mmol/l 1.3 ± 0.4 1.3 ± 0.4 1.4 ± 0.5 NS

LDL-cholesterol, mmol/l 3.8 ± 1.1 3.7 ± 1.0 4.1 ± 1.2 P=0.013

Cholesterol-HDL ratio 4.7 ± 1.6 4.7 ± 1.6 4.8 ± 1.7 NS

table 2: Occurrence of first outcome events

Outcome event N=489

Fatal or non-fatal stroke 39 (9%)

Stroke, myocardial infarction, or vascular death 57 (11.5%)

TIA or ischemic stroke 62 (12.5%)

TIA 31 (6%)

Non-fatal stroke 33 (7%)

Non-fatal myocardial infarction 6 (1%)

Vascular death 21 (4%)

Fatal stroke 8 (1.5%)

Fatal myocardial infarction 2 (0.5%)

Sudden death 10 (2%)


2

3

4

5

6H

azar

d ra

tio

Fatal or non-fatal stroke

0

1

1st34.2 cm/s(18 - 39.3)

2nd43.0 cm/s

(39.5 - 46.3)

3rd49.6 cm/s

(46.5 - 52.8)

4th56.5 cm/s(53 - 60.2)

5th72.4 cm/s

(60.8 - 155)

Quintiles of mean flow velocitymean (range)

2

3

4

5

6

Haz

ard

ratio

Major vascular events

0

1

1st34.2 cm/s(18 - 39.3)

2nd43.0 cm/s

(39.5 - 46.3)

3rd49.6 cm/s

(46.5 - 52.8)

4th56.5 cm/s(53 - 60.2)

5th72.4 cm/s

(60.8 - 155)

Haz

ard

ratio

Quintiles of mean flow velocitymean (range)

Figure 1: Hazard ratio’s for quintiles of mean flow velocity for major vascular events (stroke, myocardial infarction, or vascular death) (upper graph), and for fatal or non-fatal stroke (lower graph), adjusted for age, gender, and vascular risk factors. Values on the x-axis are mean and range in each quintile.

Chap

ter 3

.2

88Mean flow velocity

The HR of MFV for fatal or non-fatal stroke, adjusted for age and gender, did not differ between

the first four quintiles, but in the upper quintile the risk for major vascular events nearly doubled

with a HR of 1.8 (95% CI 0.7 to 4.5) although this was not statistically significant. After adjust-

ment for vascular risk factors (diabetes, hypertension, cholesterol) the HR for fatal or non-fatal

stroke did not change appreciably (HR 2.2, 95% CI 0.8 to 5.8) (Figure 1). Analyses with the MFV

at the symptomatic side showed the same relationship, but this relationship was less strong.

Because the four lower quintiles of MFV showed similar risk, these were combined and a

single cut point for the MFV was set at 60.5 cm/sec. Patients with an MFV>60.5 cm/s had a HR

for fatal or non-fatal stroke of 2.8 (95% CI 1.3 to 6.0) after adjustment for age, gender, and vascu-

lar risk factors. HR for stroke, myocardial infarction or vascular death, was 2.6 (95% CI 1.3 to 5.0)

for patients with an MFV>60.5 cm/s after adjustment for age, gender, and vascular risk factors

(Table 3). MFV and PI did not show a statistically significant relationship with the outcome event

TIA, fatal and non-fatal ischemic stroke.

Because of the possibility of increased risk with low flow, we did a more detailed analysis

of the MFV in deciles. In the lowest decile of MFV the HR for fatal or non-fatal stroke was 10.9

(95% CI: 1.3 to 88) compared to the decile with the lowest HR for fatal or non-fatal stroke (i.e.

the second decile), adjusted for age, gender, and vascular risk factors. The median velocity in

this decile was 33 cm/s (range: 18 to 36 cm/s). The HR in the 9th and 10th decile was 9.7 (95%

table 3: Relationship between TCD flow parameters, occurrence of fatal or non-fatal stroke, major vascular events and stroke or TIA in a cohort of 489 patients with a TIA or non-disabling ischemic stroke. For EDV, MFV, PSV and PI HRs with 95% confidence intervals (95% CI) of the highest quintiles compared to the risk in the lower four quintiles combined are reported, adjusted for age, gender, and major vascular risk factors.

Fatal or non-fatal stroke Major vascular events Stroke or TIA

Mean flow velocity > 60.5 cm/s 2.8 (1.3 – 6.0) 2.6 (1.3 – 5.0) 1.7 (0.9 – 3.2)

Peak systolic flow velocity > 98 cm/s 2.3 (1.1 – 4.9) 2.1 (1.1 – 3.9) 1.7 (0.9 – 3.1)

End-diastolic flow velocity >43 cm/s 2.1 (0.9 – 4.8) 2.3 (1.1 – 4.8) 1.2 (0.6 – 2.5)

Pulsatility Index >1.09 1.5 (0.7 – 3.4) 1.4 (0.7 – 2.7) 1.6 (0.8 – 3.0)

table 4: Relationship between TCD flow parameters, occurrence of fatal or non-fatal stroke, major vascular events and stroke or TIA in a cohort of 489 patients with a TIA or non-disabling ischemic stroke. For PI-MFV ratio, MFV, and PI HRs with 95% confidence intervals (95% CI) of the highest quintiles compared to the risk in the lower four quintiles combined are reported, adjusted for age, gender, and major vascular risk factors.

Fatal or non-fatal stroke Major vascular events Stroke or TIA

PI-MFV ratio 2.5 (1.4 – 4.3) 1.9 (1.2 – 3.2) 2.3 (1.4 – 3.6)

Mean flow velocity 1.7 (1.3 – 2.0) 1.6 (1.3 – 1.9) 1.4 (1.2 – 1.7)

Pulsatility Index 0.8 (0.6 – 1.0) 0.8 (0.7 – 1.0) 0.8 (0.7 – 1.0)


CI: 1.0 to 92) and 16.1 (95% CI: 1.9 to 140) respectively, again compared to the lowest decile. The

lowest decile of MFV also showed an increased risk of major vascular events (HR 2.6, 95% CI: 0.9

to 8.0), but this was not statistically significant.

PI-MFV ratio

The mean PI-MFV ratio was 2.01 (SD 0.95) and ranged from 0.46 to 8.25. Patients with a high

PI-MFV ratio were older (67 ± 11 vs 55 ± 12 years, p<0.001), were more often male (75% vs 61%,

p=0.001), and had more often hypertension (59% vs 49%, p=0.035). The HR for fatal or non-fatal

stroke was 2.5 (95% CI: 1.4 to 4.3) for 1 unit increase in PI-MFV ratio, 1.7 (95% CI: 1.3 to 2.0) per 10

m/s MFV, and 0.8 (95% CI: 0.6 to 1.0) per 0.1 unit of PI (Table 4) after adjustment for vascular risk

factors. The HR for major vascular events was 1.9 (95% CI: 1.2 to 3.2) for 1 unit increase in PI-MFV

ratio, 1.6 (95% CI: 1.3 to 1.9) per 10 m/s MFV, and 0.8 (95% CI: 0.7 to 1.0) per 0.1 unit of PI (Table

4) after adjustment for vascular risk factors. The HR for TIA, fatal and non-fatal ischemic stroke

was 2.3 (95% CI: 1.4 to 3.6) for 1 unit increase in PI-MFV, 1.4 (95% CI: 1.2 to 1.7) per 10 m/s MFV,

and 0.8 (95% CI: 0.7 to 1.0) per 0.1 unit of PI (Table 4) after adjustment for vascular risk factors.

Pulse pressure was not related to any of the outcome events, but it was associated with PI and

PI-MFV ratio (correlation coefficient 0.51, p<0.00 and 0.34, p<0.00 respectively). Adjustment for

pulse pressure did not change the hazard ratios for MFV, PI, and PI-MFV ratio.

Discussion

This cohort study of 489 patients with recent TIA or minor stroke shows that MFV and PI-MFV

ratio, measured in the MCA by TCD are independent risk factors for recurrent stroke. Interest-

ingly, MFV and PI-MFV ratio were also associated with the occurrence of major vascular events

(combined outcome measure “stroke, MI, and vascular death”). This suggests that the MFV and

PI-MFV ratio reflect not only the condition of the major cerebral blood vessels, but also that of

coronary and peripheral arteries.

Some methodological issues need to be discussed. In our study, one experienced investiga-

tor carried out all the TCD registrations, and all audiotapes were analysed by the same inves-

tigator. This excludes interobserver variability.9 We did not assess intra-observer variability,

but previous studies have shown that intra-observer variability regarding Doppler ultrasound

measurements is reasonable.10,11 Second, the MFV was a statistically significant risk factor only

after adjustment for age, gender, and other vascular risk factors (hypertension, diabetes, and

total serum cholesterol). This is probably caused by complex associations between these fac-

tors and outcome. For example, stroke risk increases with age, but when age increases, MFV

decreases.2,4,12 This was also the case in our study. Third, the association between MFV and the

occurrence of fatal and non-fatal stroke and major vascular events became statistically sig-

nificant after a dichotomization at the level of the fifth quintile. This observation was therefore

Chap

ter 3

.2

90

partly data-driven. Nevertheless, the association remained significant after alternative dichoto-

mization at the more usual cut point of 65 cm/sec. This dichotomization seems justified since

the quintiles showed a pathophysiologically plausible J-shaped relationship with the outcome

events. We did not adjust for several other vascular risk factors, most notably smoking and

presence of vascular lesions on CT, because our previous study2 did not suggest a relationship

between these factors and TCD parameters. Nevertheless, additional adjustment for these fac-

tors increased the risk ratios, and statistical significance. Fifth, in nearly 18% of our patients no

adequate acoustical window could be obtained. These patients were predominantly elderly

female patients. Although this proportion matches that of other studies,13,14 it implies that our

findings are not representative for the entire hospital population of patients with recent TIA or

stroke. Sixth, the majority of our patients underwent TCD several weeks after the index event,

when the period of very high instantaneous risk of recurrent stroke has passed. However, time

since onset of symptoms did not affect the HR for recurrent stroke or major vascular events in

our study. Finally, we excluded patients with planned carotid surgery in our study, because after

desobstruction of a symptomatic carotid stenosis, TCD findings will have changed and the risk

for vascular events will be diminished.

In our study, the risk for fatal or non-fatal stroke nearly tripled at MFV > 60.5 cm/s, suggest-

ing that the elevated risk may perhaps be due to local MCA stenoses.15 MCA stenosis of more

than 50% has been reported to be related to PSV1 and MFV.16,17. The risk of fatal or non-fatal

stroke and major vascular events was most strongly related to MFV. However, intracranial

atherosclerotic stenosis is an uncommon condition in Western Europe.16-19 Indeed, in only one

patient (0.2%) MFV exceeded the 100 cm/sec cut point for an MCA stenosis of more than 50%.

Because the negative predictive value of TCD in detecting intracranial arterial stenosis is high,

94-100%,16,17 we can safely assume that the increased risk in the upper quintile of MFV is not

caused by the presence of an MCA stenosis of more than 50%. Increased flow velocity may also

be caused by hypertension, but we adjusted for this risk factor in our analyses.

The most likely explanation, however, is that the upper quintiles of MFV in our study repre-

sent a slight but uniform narrowing of the intracranial arteries. Bos et al., who reported similar

findings in an elderly population, have argued that according to Poiseuille’s law small decreases

in diameter of the arteries caused by atherosclerotic disease have to be compensated by

relatively strong increases in blood flow.20 Increased flow itself may induce further endothelial

damage of the smaller calibre intracranial arteries, followed by inflammatory response, lipid

deposition and atherosclerotic plaque formation,21,22 especially in areas of low shear stress.23

MFV may be a more reliable indicator of this process than PSV or systolic blood pressure. There-

fore, increased flow velocity could be a subtle marker for atherosclerosis.

The prognostic value of the PI-MFV ratio is a novel finding. Previous reports have shown a

strong relationship between intracranial atheromatous disease and the combination of a high

PI and a low MFV or PSV in intracerebral vessels measured by TCD.3,24 The PI, calculated as (PSV-

EDV)/MFV, is a complex parameter thought to reflect cerebrovascular resistance. Interestingly,


PI alone was not a prognostic factor for recurrent stroke. This may suggest that cerebrovascular

resistance is only important when high cerebral blood flow cannot be maintained. A higher PI-

MFV ratio is thought to reflect diffuse intracranial stenotic disease, especially when MFV is lower

than 30 cm/s, and PI is higher than 1.2.3 Prognosis of acute stroke (<12 hours) seems to be poor

when MFV is lower than 30 cm/s.25 In our study the PI-MFV ratio was related to an increased

risk of major vascular events (combined outcome measure “stroke, MI, and vascular death”).

This may be explained by the presence of diffuse intracranial and extracranial atherosclerotic

disease. A high PI-MFV ratio may indicate higher vulnerabiltiy of the brain in case of a thrombo-

embolic event with less or lower quality collateral flow. These explanations fall beyond the

scope of the present analysis, but certainly deserve further study. Pulse pressure was associated

with PI and also with PI-MFV ratio in our study. Nevertheless, even after adjustment for pulse

pressure, the association between PI-MFV ratio and recurrent vascular events was not affected.

We further subdivided the population according to deciles of the MFV was divided in

deciles. Our results then suggested a J or U-shaped relationship of MFV with the risk for recur-

rent stroke. Other physiological parameters are also known to have a U or J-shaped relationship

with stroke and cardiovascular mortality. For example, low blood pressure as well as high blood

pressure increase risk of stroke and cardiovascular mortality.26,27

We conclude that MFV and the PI-MFV ratio, measured with TCD is an independent prognostic

factor for fatal or non-fatal stroke and major vascular events in patients with a recent TIA or

minor stroke. These parameters may not only reflect the degree of local atherosclerosis of

the cerebral arteries, but also of the general cardiovascular system. Our findings may help to

improve the prediction of recurrent stroke and other vascular events in clinical practice.

Chap

ter 3

.2

92

reFerences

1. Baumgartner RW, Mattle HP, Schroth G. Assessment of >/=50% and <50% intracranial stenoses by transcranial color-coded duplex sonography. Stroke 1999;30:87-92.


3. Sharma VK, Tsivgoulis G, Lao AY, Malkoff MD, Alexandrov AV. Noninvasive detection of diffuse intra-cranial disease. Stroke 2007;38:3175-81.




7. Bamford JM, Sandercock PA, Warlow CP, Slattery J. Interobserver agreement for the assessment of handicap in stroke patients. Stroke 1989;20:828.

8. Wijnhoud AD, Franckena M, van der LA, Koudstaal PJ, Dippel ED. Inadequate acoustical temporal bone window in patients with a transient ischemic attack or minor stroke: role of skull thickness and bone density. Ultrasound Med Biol 2008;34:923-9.


10. Baumgartner I, Behrendt P, Rohner P, Baumgartner RW. A validation study on the intraobserver and interobserver reproducibility of renal artery duplex ultrasound. Ultrasound Med Biol 1999;25:225-31.

11. Maeda H, Etani H, Handa N, Tagaya M, Oku N, Kim BH, Naka M, Kinoshita N, Nukada T, Fukunaga R, . A validation study on the reproducibility of transcranial Doppler velocimetry. Ultrasound Med Biol 1990;16:9-14.




15. Mazighi M, Tanasescu R, Ducrocq X, Vicaut E, Bracard S, Houdart E, Woimant F. Prospective study of symptomatic atherothrombotic intracranial stenoses: the GESICA Study. Neurology 2006;66:1187-91.

16. Felberg RA, Christou I, Demchuk AM, Malkoff M, Alexandrov AV. Screening for intracranial stenosis with transcranial Doppler: the accuracy of mean flow velocity thresholds. J Neuroimaging 2002;12:9-14.


17. Navarro JC, Lao AY, Sharma VK, Tsivgoulis G, Alexandrov AV. The accuracy of transcranial Doppler in the diagnosis of middle cerebral artery stenosis. Cerebrovasc Dis 2007;23:325-30.

18. Wong KS, Huang YN, Gao S, Lam WW, Chan YL, Kay R. Intracranial stenosis in Chinese patients with acute stroke. Neurology 1998;50:812-3.

19. Sacco RL, Kargman DE, Gu Q, Zamanillo MC. Race-ethnicity and determinants of intracranial athero-sclerotic cerebral infarction. The Northern Manhattan Stroke Study. Stroke 1995;26:14-20.


21. Pauletto P, Rattazzi M. Inflammation and hypertension: the search for a link. Nephrol Dial Transplant 2006;21:850-3.

22. Hansson GK. Inflammation, atherosclerosis, and coronary artery disease. N Engl J Med 2005;352:1685-95.

23. Wentzel JJ, Gijsen FJ, Stergiopulos N, Serruys PW, Slager CJ, Krams R. Shear stress, vascular remodeling and neointimal formation. J Biomech 2003;36:681-8.

24. Tian JW, Sun LT, Zhao ZW, Gao J. Transcranial color Doppler flow imaging in detecting severe stenosis of the intracranial vertebral artery: a prospective study. Clin Imaging 2006;30:1-5.

25. Halsey JH, Jr. Prognosis of acute hemiplegia estimated by transcranial Doppler ultrasonography. Stroke 1988;19:648-9.

26. Voko Z, Bots ML, Hofman A, Koudstaal PJ, Witteman JC, Breteler MM. J-shaped relation between blood pressure and stroke in treated hypertensives. Hypertension 1999;34:1181-5.

27. Leonardi-Bee J, Bath PM, Phillips SJ, Sandercock PA. Blood pressure and clinical outcomes in the International Stroke Trial. Stroke 2002;33:1315-20.

chapter 3.3Micro-embolic signals and risk of recurrent

stroke in patients with a TIA or ischemic stroke

A.D. Wijnhoud

P.J. Koudstaal

D.W.J. Dippel

Submitted for publication in the Journal of Clinical Ultrasound

Chap

ter 3

.3

96

AbstrAct

Purpose: The prognostic value of micro-embolic signals (MES) on transcranial Doppler (TCD)

ultrasound in patients with previous TIA or ischemic stroke and without significant carotid

stenosis is unknown.

Methods: TCD-investigation was performed in a cohort of 365 patients with a recent TIA or

ischemic stroke. The signal of the left and right middle cerebral artery (MCA) was recorded

for 30 minutes and was stored on digital audio tape for off-line analysis. MES were defined

according to the “Consensus on microembolus detection by TCD”. Outcome events were stroke

and major vascular events (non-fatal stroke, non-fatal myocardial infarction or vascular death).

Hazard ratio’s (HR) were estimated with Cox proportional hazards multiple regression method.

Results: Mean follow-up was 2.1 years. MES were observed in 16 (4%) patients. The occurrence

of MES increased the risk of stroke, HR 3.8 (95% CI: 1.5 to 9.9), and the risk of ischemic stroke or

TIA (HR: 2.6; 95% CI: 1.1 – 6.1). The HR for risk for major vascular events was 2.3; 95% CI: 0.9 –6.0).

Conclusion: In patients with a TIA or non-disabling ischemic stroke without severe carotid

disease, MES in the MCA are rare. Nevertheless, in these patients, MES constitute a risk factor

for recurrent stroke.

MES and vascular events after TIA or minor stroke 97

introDuction

Detection of microembolic signals (MES) with transcranial Doppler ultrasound may provide

prognostic information in addition to the conventional risk factors in patients with a TIA or

minor stroke.1 In patients with symptomatic or asymptomatic carotid stenosis, MES are associ-

ated with an increased short-term risk of stroke or TIA.2,3 It is unknown whether these results

apply to stroke patients without carotid artery stenosis.

We assessed the prognostic value of MES for recurrent stroke and other vascular events in a

consecutive cohort of patients with a previous TIA or minor stroke.

methoDs

Patients

We studied the diagnostic and prognostic value of TCD in consecutive patients with a recent

TIA or ischemic non-disabling stroke prospectively, from April 1999 until March 2003. Nearly

all patients were included in our hospital, 22 were included in Meander Medisch centrum in

Amersfoort. Inclusion criteria were a TIA or non-disabling ischemic stroke in the preceding 6

months, corresponding with grade 3 or better on the modified Rankin scale.4 Patients had to be

over 18 years of age, and had to give informed consent. We excluded patients in whom carotid

surgery or stenting was planned. These patients were excluded because carotid artery stenosis

is related to the presence of MES.{Molloy, 1999 25 /id} Patients with known atrial fibrillation, and

patients with mechanical heart valves were also excluded, since in these patients MES occur

frequently, and are thought to be gaseous, not solid.{Georgiadis, 1998 208 /id} The study was

approved by the Medical Ethics Committee and Review Board of the Erasmus MC in Rotterdam,

the Netherlands.

tcD recordings

All patients underwent TCD examination (Multidop X-4, DWL, Sipplingen, Germany). TCD

examination was performed within 6 months after TIA or non-disabling ischemic stroke by

one investigator (A.W.). The middle cerebral artery (MCA) was insonated bilaterally. For MES

detection, the signal was recorded for 30 minutes and stored on digital audio tape (ADAT-LX20,

Alesis, Santa Monica, California) for off-line analysis. This analysis was also performed by one

investigator (A.W.), who was blinded to other clinical data and to the occurrence of outcome

events, during off-line analysis. The intensity, depth and side of the MES were registered. MES

were defined according to the Consensus on Microembolus Detection by TCD.5

Chap

ter 3

.3

98



out hemorrhage, an ECG, and a duplex-ultrasound scan of the carotid arteries in case of an

anterior circulation stroke. Risk factors (diabetes, smoking, hypertension, serum cholesterol

level) were assessed as described previously.6

outcomes

The primary outcome event was fatal or non-fatal stroke (“stroke”). Secondary outcome events

were the composite of non-fatal stroke, non-fatal myocardial infarction and death from all

vascular causes (“major vascular events”), whichever occurred first.

Follow-up was done annually by telephone survey by an experienced nurse who was

blinded for the TCD results. All possible events were adjudicated by two experienced vascular

neurologists.


The cumulative probability of composite outcome events was estimated with Kaplan-Meier

survival analysis. Hazard ratios (HR) with 95% confidence intervals (CI) for MES were estimated

with Cox proportional hazards regression.

resuLts


We included 598 consecutive patients in our study. In 4 patients, the diagnosis was revised

shortly after inclusion. Exactly 105 of the remaining 594 patients had two-sided window failure.

Because of technical problems or because they did not tolerate the headband, 124 patients

did not complete the 30 minute registration. The remaining 365 patients were included in the

present analysis (Table 1).


Mean time between index event and TCD examination was 53 ± 49 days (range 1-207), and

did not differ between patients with MES and patients without MES (38 ± 43 vs 53 ± 48 days,

p=0.21). MES occurred in 16 patients (4 %). The mean number of MES was 7 (range 1 to 37).

outcome events

Mean follow-up was 2.3 years (range 17 days to 5.7 years). The two-year cumulative incidence

was 10% for stroke and 13% for major vascular events.


micro-embolic signals

The risk for stroke was increased in patients with MES, HR 3.8 (95% CI: 1.5 to 9.9). The HR for

major vascular events was 2.3 (95% CI: 0.9 to 6.0). The occurrence of MES was not related to time

between TIA or stroke and TCD examination (Figure 1).

The risk for stroke was increased with the number of observed MES per patient, HR 1.11 (95%

CI: 1.01 to 1.22 per single observed MES). Adjustment for age, gender, and vascular risk factors

did not attenuate this association. One patient with a symptomatic carotid artery occlusion and

an asymptomatic artery stenosis had 37 MES in 30 minutes on the asymptomatic side. Because

this patient was initially not intended to undergo a carotid endarterectomy, we included him in

the study. Exclusion of this patient did not change our results.


Overall N=365 No MES N=349 MES N=16

Demographics

Age, years (mean ± SD) 59 ± 13 59 ± 13 59 ± 10 NS

Male gender 243 (67%) 229 (66%) 14 (88%) P=0.07

Caucasian 313 (87%) 298 (87%) 15 (94%) NS


TIA 187 (51%) 179 (51%) 8 (50%) NS

Anterior circulation 286 (78%) 271 (78%) 15 (94%) NS

Lacunar syndrome 134 (36%) 124 (36%) 10 (63%) P=0.029

CT characteristics

Any infarct on CT scan 171 (47%) 163 (47%) 8 (50%) NS

White matter lesions on CT scan 52 (14%) 50 (14%) 2 (13%) NS

Risk factors

Smoking, current 100 (27%) 95 (27%) 5 (31%) NS

Hypertension 189 (52%) 182 (52%) 7 (44%) NS

Diabetes 53 (15%) 52 (15%) 1 (6%) NS


Previous myocardial infarction 45 (12%) 45 (13%) 0 (0%) NS

Carotid artery stenosis (≥70%) 25 (7%) 24 (7%) 1 (6%) NS

table 2: Relationship between MES and relative risk of fatal or non-fatal stroke, major vascular events, and stroke or TIA in a cohort of 365 patients with a TIA or non-disabling ischemic stroke.

Hazard ratio (95% Confidence Interval)

Fatal or non-fatal stroke 3.8 (1.5 – 9.7)

Major vascular events 2.3 (0.9 – 6.0)

Stroke or TIA 2.6 (1.1 – 6.1)

Chap

ter 3

.3

100

Discussion

This study indicates that MES in the MCA measured by TCD increase the risk of stroke almost

fourfold. MES were present in only 4% of the patients.

Some methodological issues need to be discussed. In our study, one experienced investiga-

tor carried out all the TCD registrations, and all tapes were analysed by the same investigator.

This excludes interobserver variability. Second, 17.7% of our patients had a bilateral inadequate

acoustical window. These patients were predominantly elderly female patients. Although this

proportion matches that of other studies,7 it implies that our findings are not representative

for the entire hospital population of patients with previous TIA or stroke. The majority of our

patients underwent TCD several weeks after their TIA or stroke, that is, beyond the period with

the highest risk of recurrent stroke. However, time since onset of symptoms did not affect the

HR for recurrent stroke or major vascular events.

In the patients without a carotid artery stenosis or atrial fibrillation it is not clear what the

origin of the MES is. However, MES constitute a risk factor for stroke and major vascular events,

regardless of the origin.

Only 4% of our patients had MES. This low prevalence was not surprising since MES most

frequently occur in patients with a carotid artery stenosis8 and we had excluded patients with a

planned carotid surgery in our study, because after surgery for a symptomatic carotid stenosis,

the risk of ischemic stroke diminishes, which would make our results more difficult to interpret.

MES most often occur in the acute phase after stroke,9 whereas our patients were predomi-

nantly examined in the subacute or chronic phase. Nevertheless, MES were still related to a

60

80

100

120

140

Num

ber o

f pat

ient

s

MES

No MES

8%

1%

2%

0

20

40

1 2 3 4 5 6

Num

ber o

f pat

ient

s

Time since index event (in months)

6%

6% 0%

Figure 1: Number of patients with MES in relation to time from index event to TCD examination in a series of 365 patients with a TIA or ischemic stroke.


recurrent fatal or non-fatal stroke. Idicula et al.10 showed that MES are frequent in acute stroke,

with MES present in 25% of the patients. MES were, however, in the acute phase not related to

a recurrent vascular event. It is therefore likely that the mechanism of MES is in the acute phase

different from the chronic phase.

In patients with a carotid artery stenosis, either symptomatic or asymptomatic, MES were

related to increased risk of ipsilateral stroke. As far as we know, this has not been investigated

in an unselected series of patients with stroke until now. In our study, only one of the patients

with MES had carotid artery stenosis, and leaving that patient out of the statistical analysis did

not change the results.

We conclude that in patients with a TIA or non-disabling ischemic stroke, even in the absence

of a carotid artery stenosis, MES constitute a risk factor for recurrent stroke.

Chap

ter 3

.3

102

reFerences

1. Hankey GJ. Long-term outcome after ischaemic stroke/transient ischaemic attack. Cerebrovasc Dis 2003;16 Suppl 1:14-9.:14-9.


3. Markus HS, King A, Shipley M, Topakian R, Cullinane M, Reihill S, Bornstein NM, Schaafsma A. Asymp-tomatic embolisation for prediction of stroke in the Asymptomatic Carotid Emboli Study (ACES): a prospective observational study. Lancet Neurol 2010;9:663-71.





8. Koennecke HC, Mast H, Trocio SHJ, Sacco RL, Ma W, Mohr JP, Thompson JL. Frequency and deter-minants of microembolic signals on transcranial Doppler in unselected patients with acute carotid territory ischemia. A prospective study. Cerebrovasc Dis 1998;8:107-12.

9. Sliwka U, Lingnau A, Stohlmann WD, Schmidt P, Mull M, Diehl RR, Noth J. Prevalence and time course of microembolic signals in patients with acute stroke. A prospective study. Stroke 1997;28:358-63.


chapter 3.4Improving prediction of major vascular events

in patients with a TIA or ischemic stroke with transcranial Doppler ultrasonography

A.D. Wijnhoud

H.F. Lingsma

E.W. Steyerberg

P.J. Koudstaal

D.W.J. Dippel

Submitted for publication in Stroke

Chap

ter 3

.4

106

AbstrAct

Background: Prediction models are important for long-term vascular events in patients with

a recent TIA or ischemic stroke. We aimed to study the incremental value of micro-embolic

signals (MES) and flow velocity parameters measured with transcranial Doppler (TCD) over

clinical variables alone in predicting recurrent vascular events.

Methods: The cohort consisted of 592 patients with a TIA or minor stroke, with a mean follow-up

of 2 years. Mean flow velocity (MFV) could be measured in 489 of these patients in both middle

cerebral arteries. Micro-embolic signals were recorded for 30 minutes and were analysed off-

line in 365 patients. Outcomes were the composite of non-fatal stroke, myocardial infarction or

vascular death (Major vascular events) with a two-year risk of 13%, and the composite of fatal or

non-fatal stroke (Stroke) with a two-year risk of 10%. We used calibration graphs, the c-statistic,

and the Net Reclassification Index (NRI) to evaluate the effect of adding TCD parameters to the

ABCD2 clinical prediction model.

Results: Adding MES and high mean flow velocity to the ABCD2 score improved the discrimina-

tion for both models, with increasing c-statistic from 0.62 to 0.69 (p<001) for major vascular

events, and from 0.61 to 0.71 (p<0.01) for fatal or non-fatal stroke. The NRI was 0.31 (95% CI 0.01

to 0.60) for prediction of major vascular events, and 0.42 (0.07 to 0.77) for prediction of fatal or

non-fatal stroke.

Conclusion: Information concerning micro-embolic signals and mean flow velocity on TCD

modestly improves the prediction of models for the recurrence of fatal or non-fatal stroke.

Further studies are necessary on the validity and clinical application of these models.

Improving prediction with TCD after TIA or minor stroke 107

introDuction

Patients with a recent stroke have an increased long-term risk of new cerebrovascular and

cardiovascular events. In a previous study, we showed that the ABCD2 prediction model is most

useful compared to other available models for prediction of long term risk in these patients.

However, the discrimination between patients with high and low risk of recurrent stroke could

be much improved.1 Micro-embolic signals and flow velocity parameters measured with tran-

scranial Doppler ultrasonography are prognostic factors for cerebrovascular and cardiovascular

events in patients with a recent TIA or ischemic stroke with2 and without3 carotid artery steno-

sis. The prognostic value of MES or the flow velocity parameters measured with TCD have not

yet been studied in a long-term prediction model.

methoDs

We studied patients from a prospective cohort study of the diagnostic and prognostic value of

TCD in patients with a recent TIA or ischemic non-disabling stroke as described in a previous

study.[2] In brief, inclusion criteria were a recent (<6 months) TIA or non-disabling ischemic

stroke of presumed arterial origin. Patients had to be over 18 years of age, and had to give

informed consent. Patients had to be independent in most activities of daily living, correspond-

ing with grade 3 or better on the modified Rankin scale.4 We excluded patients with planned

carotid surgery or stenting, because the risk of recurrent events would be affected by the treat-

ment. For similar reasons, we excluded patients with mechanical heart valves. The study was

approved by our Medical Ethics Committee and Review Board.

Procedure and definitions

The primary outcome was the composite end point of stroke, myocardial infarction and vascu-

lar death. The secondary outcome was the composite end point of fatal or non-fatal stroke. In

the validation cohort, stroke was defined as a focal neurological deficit, resulting in disability for

more than 24 hours, confirmed by a neurologist, with CT scan, if possible.

Myocardial infarction was defined as an episode of precordial chest pain accompanied

by ECG evidence of recent infarction, and/or release of cardiac enzymes. Vascular death was

death within 4 weeks after stroke or MI, or sudden death. Follow-up was done annually by

telephone survey by an experienced research nurse. If patients reported any hospital visits or

any symptoms suggesting a vascular event, their treating physician was contacted for further

information or discharge letters. In the validation cohort Kaplan-Meier analysis of survival was

used to estimate the two-year risk of the primary and secondary outcome.

Chap

ter 3

.4

108

tcD recordings

All patients underwent TCD examination (Multidop X-4, DWL, Sipplingen, Germany). All TCD

recordings were carried out by one investigator (A.W.). TCD examination was performed within

6 months after TIA or non-disabling ischemic stroke. In all patients, peak systolic flow veloc-

ity (PSV) and end-diastolic flow velocity (EDV) was measured with a handheld 2 MHz probe

in both middle cerebral arteries (MCA). Mean flow velocity (MFV) was calculated as EDV +

1/3(PSV-EDV). For MES detection, the signal was recorded for 30 minutes and stored on digital

audio tape (ADAT-LX20, Alesis, Santa Monica, California) for off-line analysis. This analysis was

also performed by one investigator (A.W.), who was blinded to other clinical data and to the

occurrence of outcome events. During off-line analysis, the intensity, depth and side of the MES

were registered. MES had to meet the following criteria: MES are transient, last less than 300

milliseconds, are unidirectional within the Doppler velocity spectrum, are accompanied by a

“snap”, “chirp”, or “moan” on the audible output and their amplitude is at least 3 dB higher than

that of the background blood flow velocity spectrum.5


MFV was dichotomized at 60.5 cm/s since MFV > 60.5 cm/s increases risk of major vascular

events and stroke in patients with a TIA or ischemic stroke.3 We estimated the actual two-year

risk of primary and secondary outcome events for each patient in the validation cohort using

Kaplan-Meier survival analysis. For missing values, the mean value of a variable was imputed.

We then calculated the two-year risk as predicted by the ABCD2 prediction model in a Cox’s

proportional hazard model The equation was adjusted for the mean cumulative hazard and for

the prevalence of risk factors in the validation cohort, as recommended by several authors.6,7

We then added the TCD parameters MES and MFV>60.5 cm/s to this model.


Two aspects of validity were examined: calibration and discrimination. Calibration, measures

how closely predicted outcomes agree with actual outcomes. Discrimination refers to the

ability to distinguish patients who will have an outcome event and those who will not.8 The

predicted probabilities of vascular events should be trustworthy (calibration) and extreme

(discrimination).

We constructed calibration plots, in which observed two-year outcome was plotted against

predicted two-year risk, using a Kaplan-Meier survival curve and the ABCD2 prediction rule,

with and without the TCD parameters. We indicate outcome by quintiles of predicted prob-

abilities. Calibration curves can be approximated by a regression line (or calibration line) with

intercept (α) and slope (β). Well-calibrated models have α=0 and β=1. We calculated slopes for

each prediction model. Discrimination was quantified with the concordance (c)-statistic, taking

censored observations into account. The c-statistic resembles the area under the ROC curve. A

c-statistic of 1 implies a test with perfect sensitivity and specificity, while a value of 0.5 implies


that the model predictions are no better than chance.8 Statistical significance of improvements

of the model was analysed by chi square analysis of the log likelihood ratio, with appropriate

degrees of freedom. We also calculated the Net Reclassification Index (NRI). The NRI measures

the proportion of patients with an improved prediction minus the proportion of patients with

a worse prediction after adding the TCD parameters to the ABCD2 model. A positive NRI means

improvement of the model.

resuLts


We included 598 consecutive patients in our study. The study population consisted of patients

for whom no other treatment than risk factor modification and antiplatelet medication was

available. In 4 patients, the diagnosis was revised shortly after inclusion (1 patient had multiple

sclerosis, 2 had focal epileptic seizures and 1 had migraine with aura). In 105 (17.8%) of the

remaining 594 patients, we failed to obtain adequate Doppler data due to two-sided window

failure. Therefore, in 489 patients (82.2%) we obtained adequate data for flow velocity measure-

ments (i.e. mean flow velocity). A total of 114 (19%) did not complete the 30 minute registration

because of technical problems or because they did not tolerate the headband. The remaining

365 patients (61.5%) were included in the analysis of MES. The baseline characteristics are

described in Table 1.


Mean time between index event and TCD examination was 53 ± 49 days (range 1-207), and

did not differ between patients with MES and patients without MES (38 ± 43 vs 53 ± 48 days,

p=0.21). MES occurred in 16 patients (4 %). The mean number of MES was 7 (range 1 to 37).

Mean MFV was 51.1 ± 14.4 cm/sec. MFV was negatively related to age, and was lower in men,

whereas diabetes and total serum cholesterol was positively related to MFV in this study, as

described in a previous study of the same study population.9

outcome events

Mean follow-up was two years and one month (range 17 days to 5.7 years). Two-year-risk was

13% for major vascular events and 10% for fatal or non-fatal stroke.


The ABCD2 prediction model overestimated the risk of recurrent vascular events (Table 2 and

Fig 1). Adding MES improved calibration of the model (p=0.036), but not discrimination for

major vascular events (Table 2). Adding MES to the prediction model for stroke improved the

model (p=0.03), and also improved discrimination (delta c=0.04, p<0.02). Adding MFV>60.5

Chap

ter 3

.4

110


Patients All N=594 With successful TCD registration N=365

Demographics

Age, years (mean ± SD) 62 ± 13 59 ± 13

Male gender 353 (59%) 243 (67%)

Caucasian 495 (83) 313 (87%)


TIA 322 (54%) 187 (51%)

Anterior circulation 477 (80%) 286 (78%)

Lacunar syndrome 214 (36%) 134 (36%)

CT characteristics

Any infarct on CT scan 276 (46%) 171 (47%)

White matter lesions (CT) 91 (15%) 52 (14%)

Risk factors

Smoking, current 155 (26%) 100 (27%)

Hypertension 312 (53%) 189 (52%)

Diabetes 99 (17%) 53 (15%)

Previous TIA or stroke 123 (21%) 83 (23%)

Previous myocardial infarction 62 (10%) 45 (12%)

Carotid artery stenosis (≥70%) 44 (7%) 25 (7%)

table 2. Effect of adding MES, MFV>60.5 cm/s, and both to ABCD2 prediction model in patients with successful TCD registration (n=365).

Calibration DiscriminationNRI

Slope [95% CI] c-statistic [95% CI]

Major vascular events

ABCD2 alone 0.88 [0.04–1.17] 0.62 [0.54–0.70 ]

Model including MES 1.16 [0.5–1.76] 0.66 [0.58–0.74] 0.12 [-0.17–0.42]

Model including MFV>60.5 cm/s 1.15 [0.60–1.70] 0.64 [0.57–0.72 ] 0.21 [-0.08–0.51]

Model including MES and MFV>60.5 cm/s 1.25 [0.57–1.94] 0.69 [0.61–0.76 ] 0.31 [0.01–0.60]

Stroke

ABCD2 alone 0.82 [-0.43–2.07] 0.61 [0.52–0.71]

Model including MES 1.26 [0.67–1.86] 0.66 [0.57–0.75 ] 0.21 [-0.13–0.59]

Model including MFV>60.5 cm/s 1.03 [0.36–1.70] 0.65 [0.57–0.73 ] 0.25 [-0.10–0.60]

Model including MES and MFV>60.5 cm/s 1.04 [0.29–1.78] 0.71 [0.62–0.80 ] 0.42 [0.07–0.77]


cm/s to the ABCD2 improved the model, but just not significantly (p=0.054) for major vascular

events. Discrimination however, improved (p<0.02). Adding MFV>60 cm/s improved the model

for stroke, but not significantly (p=0.079).

When both MES and MFV>60.5 cm/s were added to the ABCD2 prediction model using

the prognostic sum score, both parameters improved of the model for major vascular events

(p=0.037 for MES, and p=0.021 for MFV>60.5 cm/s. HR for the presence of MES in this model

was 2.67 (95% CI: 1.06 to 6.73), and HR for MFV>60.5 cm/s was 2.04 (95% CI: 1.11 to 3.74) for

the outcome event major vascular events. Discrimination improved from 0.62 to 0.69 (p<0.01).

The NRI was positive, 0.31 (0.01-0.60), which means a significiant improvement of the model.

Both MES and MFV improved the model for stroke (p=0.003 for MES, and p=0.029 for MFV>60.5

cm/s). For the outcome event fatal or non-fatal stroke, the HR for MES was 4.21 (95% CI: 1.63 to

0,2

0,25

0,3

0,35

0,4

0,45

0,5

Obs

erve

d pr

opor

tion

of m

ajor

vas

cula

r eve

nts

ABCD2 alone

0

0,05

0,1

0,15

0,2

0 0,1 0,2 0,3 0,4 0,5

Obs

erve

d pr

opor

tion

of m

ajor

vas

cula

r eve

nts


0,2

0,25

0,3

0,35

0,4

0,45

0,5

Obs

erve

d pr

opor

tion

of m

ajor

vas

cula

r eve

nts

Model including MES and MFV>60.5 cm/s

0

0,05

0,1

0,15

0,2

0 0,1 0,2 0,3 0,4 0,5

Obs

erve

d pr

opor

tion

of m

ajor

vas

cula

r eve

nts


(A)

0,2

0,25

0,3

0,35

0,4

0,45

0,5

Obs

erve

d pr

opor

tion

of s

trok

e

ABCD2 alone

0

0,05

0,1

0,15

0,2

0 0,1 0,2 0,3 0,4 0,5

Obs

erve

d pr

opor

tion

of s

trok

e

Eestimated probability of stroke

0,2

0,25

0,3

0,35

0,4

0,45

0,5O

bser

ved

prop

ortio

n of

str

oke

Model including MES and MFV>60.5 cm/s

0

0,05

0,1

0,15

0,2

0 0,1 0,2 0,3 0,4 0,5

Obs

erve

d pr

opor

tion

of s

trok

e


(b)

Figure 1. Calibration graph: Mean predicted probabilities (X-axis) versus observed frequencies (Y-axis) of the composite outcome event of non-fatal stroke, non-fatal myocardial infarction or vascular death (A) based on ABCD2 score with and without TCD parameters, of the composite outcome event fatal or non-fatal stroke (B) based on the ABCD2 score with and without MES and MFV>60.5 cm/s.

Chap

ter 3

.4

112

10.87), the HR for MFV>60.5 cm/s was 2.23 (95% CI: 1.08 to 4.57). Discrimination improved from

0.61 to 0.71 (p<0.01). The NRI was again positive, 0.42 (0.07-0.77).

Discussion

This study shows that MES and a MFV> 60.5 cm/s in the MCA are independent prognostic fac-

tors for long term prognosis in patients with a recent TIA or minor ischemic stroke when added

to the ABCD2 prediction model. Moreover, adding these two factors to the ABCD2 prediction

model improves calibration as well as discrimination. For a 70-yr old patient with hypertension

but no diabetes, and a hemiparesis lasting longer than 60 minutes, the two-year risk would be

14%, for the same patient with MES and a MFV>60 cm/s in the MCA the two-year risk would be

28%, without MES and increased MFV, his two-year risk would amount to 19%.

Some limitations of this study have to be discussed. First, although the validation cohort

was of reasonable size (598 patients), the effective sample size was not large, with 57 major

vascular events, and 41 fatal or non-fatal strokes. Because of window failure and intolerance

to the headband, not all patients were included in the final analyses which made the effective

sample size even smaller. Our validation cohort was also our derivation cohort. This influences

calibration, which is usually better based on the derivation cohort instead of an independent

sample. It will be very interesting to see if our results can be replicated in other studies.

Although the ABCD2 prediction model was intended for short-term prognosis, external

validation of the ABCD2 score shows reasonable calibration and discrimination.1 Holzer et al.

demonstrated that an ABCD2 score > 3 was associated with an increased risk for vascular events

for medium- to long-term prognosis.10

TCD parameters have not been added to the ABCD2 score to improve prediction of stroke or

other vascular events before. Adding brain infarction or carotid imaging to the ABCD2 model

improves the prediction of stroke after TIA in the acute phase.11,12 However, for long-term

prognosis of the ABCD2 score no attempts of improvement have yet been made.

Conclusion: MES and MFV>60.5 cm/s improve prediction of recurrent vascular events in

patients with a TIA or minor ischemic stroke when added to the ABCD2 prediction model.


reFerences

1. Wijnhoud AD, Maasland L, Lingsma HF, Steyerberg EW, Koudstaal PJ, Dippel DW. Prediction of major vascular events in patients with transient ischemic attack or ischemic stroke: a comparison of 7 models. Stroke 2010;41:2178-85.


3. Wijnhoud AD, Koudstaal PJ, Dippel DW. The prognostic value of pulsatility index, flow velocity, and their ratio, measured with TCD ultrasound, in patients with a recent TIA or ischemic stroke. Acta Neurol Scand 2011;10-0404.



6. Steyerberg EW, Bleeker SE, Moll HA, Grobbee DE, Moons KG. Internal and external validation of predic-tive models: a simulation study of bias and precision in small samples. J Clin Epidemiol 2003;56:441-7.

7. D’Agostino RB, Sr., Grundy S, Sullivan LM, Wilson P. Validation of the Framingham coronary heart disease prediction scores: results of a multiple ethnic groups investigation. JAMA 2001;286:180-7.



10. Holzer K, Feurer R, Sadikovic S, Esposito L, Bockelbrink A, Sander D, Hemmer B, Poppert H. Prognostic value of the ABCD2 score beyond short-term follow-up after transient ischemic attack (TIA)--a cohort study. BMC Neurol 2010;10:50.:50.

11. Giles MF, Albers GW, Amarenco P, Arsava MM, Asimos A, Ay H, Calvet D, Coutts S, Cucchiara BL, Dem-chuk AM, Johnston SC, Kelly PJ, Kim AS, Labreuche J, Lavallee PC, Mas JL, Merwick A, Olivot JM, Purroy F, Rosamond WD, Sciolla R, Rothwell PM. Addition of brain infarction to the ABCD2 Score (ABCD2I): a collaborative analysis of unpublished data on 4574 patients. Stroke 2010;41:1907-13.

12. Merwick A, Albers GW, Amarenco P, Arsava EM, Ay H, Calvet D, Coutts SB, Cucchiara BL, Demchuk AM, Furie KL, Giles MF, Labreuche J, Lavallee PC, Mas JL, Olivot JM, Purroy F, Rothwell PM, Saver JL, Sheehan OC, Stack JP, Walsh C, Kelly PJ. Addition of brain and carotid imaging to the ABCD(2) score to identify patients at early risk of stroke after transient ischaemic attack: a multicentre observational study. Lancet Neurol 2010;9:1060-9.

chapter 4General discussion

General discussion 117

In this thesis, I have studied the value of transcranial Doppler ultrasonography (TCD) in patients

with a recent TIA or ischemic stroke. In this Chapter, I will summarize the main findings, discuss

methodological issues, review the results in the broader perspective of their clinical application

and discuss their clinical relevance. Finally, I will provide suggestions for further research.

My research questions were:


embolism and small vessel disease in patients with a TIA or minor ischemic stroke?


minor ischemic stroke by means of TCD investigation? If so, can TCD improve prediction

models?

mAin FinDings

Diagnostic value of transcranial Doppler ultrasonography

I found that TCD parameters have a complex relationship with vascular risk factors such as age,

hypertension and diabetes. I investigated these relationships, because these vascular risk fac-

tors may confound the association between TCD results and recurrent vascular events. 1-3 One

of our main goals was to investigate if TCD parameters such as flow velocities can be of more

diagnostic and prognostic value in predicting vascular outcome events than these vascular risk

factors alone. In the patients participating in the study, blood flow velocity in the middle cere-

bral artery (MCA) decreased with age, and was lower in men than in women. Blood flow velocity

in the MCA increased with total serum cholesterol, and was increased in diabetics compared

to non-diabetics. Cerebrovascular CO2-reactivity was lower in hypertensive patients. Cerebral

CO2-reactivity decreased with increasing total serum cholesterol (Chapter 2.1).

I found that micro-embolic signals (MES) were more often present in patients with a non-

lacunar stroke than in patients with a lacunar stroke. MES were more often present in the acute

phase of TIA or ischemic stroke than in the chronic phase. MES could not discriminate between

patients with and without a potential cardiac source of embolism (PCSE) (Chapter 2.3) which

was one of the main questions of this thesis. In our large cohort of patients, MES were present

in only 4% of the patients.

Prognostic value of transcranial Doppler ultrasonography

Mean Flow velocity

Mean flow velocity (MFV) in the MCA is an independent risk factor for recurrent stroke. I found

that patients with an MFV of more than 60.5 cm/s (the upper quintile) had 3 times increased

Chap

ter 4

118

risk of recurrent stroke or other major vascular events compared with the other patients. This

relationship was not influenced by other vascular risk factors (Chapter 3.2).

PI-MFV ratio

MFV was related to pulsatility index (PI), which is a measure of peripheral vascular resistance.

The PI is calculated as PSV-EDV/MFV. Our results showed that PI decreased strongly when MFV

increased, and both were associated with recurrent stroke. Because of this interaction, I created

a new factor, the PI-MFV ratio which is the PI divided by the MFV, and therefore ((PSV-EDV)/

MFV2). The PI-MFV ratio was clearly related to other vascular risk factors. Patients with a high

PI-MFV ratio were older, were more often male, and had more often hypertension. But even

after adjustment for these risk factors, which are potential confounders, the PI-MFV ratio was

associated with a higher risk of recurrent stroke or other vascular events, even stronger than

the PI (Chapter 3.2).

Micro-embolic signals

Patients with MES had an almost fourfold increased risk of stroke in my study population. This

risk applied to patients without a carotid artery stenosis. More surprisingly, I found that patients

with MES also had an increased risk of other major vascular events such as myocardial infarc-

tion or vascular death (Chapter 3.3). The prevalence of MES was low however, compared to the

prevalence in patients with symptomatic carotid stenosis; MES were only present in 4% of the

patients.

improvement of prediction

In order to improve prediction in patients with stroke and TIA, we first compared 7 prediction

models to determine which provided the most adequate estimation of the long-term risk

for cardiovascular or cerebrovascular events. I compared external validity, i.e. calibration and

discrimination, of population based models and of stroke-cohort based models (Chapter 3.1).

Calibration, or reliability, measures how closely predicted outcomes agree with actual out-

comes. Discrimination refers to the ability to distinguish patients with and without outcome

events. Overall, we found that the ABCD2 study performed best and was most easily clinically

applicable (Chapter 3.1). I therefore chose the ABCD2 study to evaluate whether prediction

of long-term risk of patients with a TIA or minor stroke could be improved by adding TCD

parameters.

The ABCD2 prediction model includes 5 parameters: Age, Blood pressure, Clinical features (i.e.

aphasia, unilateral weakness, or other symptoms), Duration of the symptoms, and Diabetes.

These parameters are easy to assess and this model is therefore very easy to use. This model

was originally designed to predict short term risk: 2 days, 7 days, and 30 days. I found that

this model was also applicable to predict recurrent stroke or other major vascular events in 2


years. This model performed better when the before mentioned TCD parameters were added

(Chapter 3.4).

Adding the presence of MES as well as the upper quintile of MFV separately to the ABCD2

prediction model improved both its calibration and discrimination, though not significantly.

If both were added simultaneously calibration and discrimination for prediction of recurrent

stroke and other vascular events were significantly improved (Chapter 3.4).

Discrimination measured by c-statistic improved from 0.62 to 0.69 (p<0.01) for major vascular

events, and from 0.61 to 0.71 (p<0.01) for recurrent stroke. The Net Reclassification Index (NRI)

was 0.31 (95% CI: 0.01 to 0.60) for the prediction of major vascular events. The NRI was 0.42

(95% CI: 0.07 to 0.77) for the prediction of recurrent stroke (Chapter 3.4). The NRI measures the

proportion of patients with an improved prediction minus the proportion of patients with a

worse prediction after adding the TCD parameters to the ABCD2 model. A positive NRI means

improvement of the prediction model.

Window failure

In my study, TCD registration was not successful in all patients. Nearly 18% of the patients had

two-sided window failure (WF), e.g. the failure of the ultrasound signal to pass through the

temporal bone. I found that age and female gender were strongly related to WF. The skull thick-

ness at the level of the temporal window was related to inadequacy of the ultrasound signal

causing WF. A decreased radiodensity of the bone at the temporal window was also related to

WF, but not significantly so, after adjustment for age and gender (Chapter 2.2).

methoDoLogicAL consiDerAtions

study population and selection bias

We prospectively studied a large cohort of consecutive patients with a recent TIA or minor

ischemic stroke corresponding with grade 3 or less on the modified Rankin scale.4 We excluded

patients with a carotid artery stenosis who were planned for carotid surgery. These patients

were excluded because carotid artery stenosis is related to the presence of MES,5 diminished

cerebral CO2-reactivity,6 and altered flow velocities in the middle cerebral artery.7 Both TCD

parameters and risk of recurrent events would be affected by the carotid surgery, which would

make our results more difficult to interpret. We also excluded patients with mechanical heart

valves, since in these patients MES occur frequently, and are thought to be gaseous, not solid.8

It may seem that exclusion of these patients can lead to selection bias, but in these particular

patients subgroup, the value of TCD was already clear. These subgroups were therefore not of

interest. Our study was designed to explore the value of TCD in the rest of the stroke popula-

tion. We aimed for 800 patients, but inclusion was slower than expected. Therefore, only 598

Chap

ter 4

120

patients were included, but we prolonged the duration for follow-up, which resulted in more

outcome events and hence sufficient statistical power.

Although our proportion window failure of 18% matches that of other studies,9,10 it implies that

our findings are not representative for the entire hospital population of patients with recent

TIA or stroke. This kind of selection bias is unavoidable. Of the patients with successful TCD

registration, only 4 were lost to follow-up.

Patients were included in the study from 1999 to 2002. Risk of recurrent vascular events has

declined over the past 50 years.11 Risk of recurrent vascular events in patients with a TIA or

ischemic stroke today is therefore very likely to be lower than 10 year ago at the time of our

study period. The declined risk of recurrent vascular events can be attributed to a better treat-

ment of hypertension and hypercholesterolemia.11 In the past ten years the preventive effect

of statins12 and antihypertensive drugs13 in patients with vascular disease has been sufficiently

proven. The prevalence of these risk factors has not decreased, but treatment has improved.

Patients with a TIA or ischemic stroke are currently more often treated with statins and antihy-

pertensive drugs according to current guidelines. More recently, the ESPRIT study showed that

adding dipyridamole to aspirin for secondary prevention led to a further reduction of recurrent

vascular events of 1% per year.14 It is not likely that my conclusions about the role of MES and

flow velocity will be affected by these developments, because it concerns relative risk estimates.

However, the calibration of our prediction model may be affected by the lower overall risk of

recurrent vascular events, and it may have to be adapted before applying it to new populations.

tcD recordings

In our study, one experienced investigator carried out all the TCD registrations, and all audio-

tapes were analysed by the same investigator. This excludes interobserver variability.15 We did

not assess intra-observer variability, but previous studies have shown that intra-observer vari-

ability regarding Doppler ultrasound measurements is reasonable.16,17 One investigator was

involved in analysis of TCD registrations and in analysis of outcome events. In order to maintain

blinded assessment the outcome events were anonimized.

Our results showed that window failure was related to bone thickness and bone density (Chap-

ter 2.2). Our definition of window failure was the failure to develop en envelop around the

TCD signal when using the headband. One could argue that this is still subjective, but to our

opinion, no clearer definition is present.

tcD validation

Confounding is present when a factor is associated with both the determinant and the out-

come. We have not performed any other tests to evaluate the cerebral circulation. There may


be unobserved confounding in our study. A stenosis of the middle cerebral artery (MCA) is

such a potential confounder. Blood flow velocity is related to vessel diameter, it increases when

the vessel diameter decreases. However, only one patient met the criteria for an MCA stenosis

of more than 50%.18 Excluding this patient from the analysis did not change our results. It is

therefore very unlikely that our results were influenced by the presence of an MCA stenosis.

Prognostic value

The identification of prognostic factors in a multivariable model is essentially not the same as

prediction. These two terms can be confusing. When a factor is related to outcome events, and

therefore occurs more often in patients with an outcome event than in patients without the

outcome event, it means that this factor is a prognostic factor in patients. It does not mean,

however, that one can estimate the individual risk of an outcome event more precisely. The

estimation of individual risks in patients is called prediction. We have first investigated whether

TCD parameters were prognostic factors (Chapter 3.2), and after that, we investigated whether

these factors could contribute to the prediction of recurrent events by adding the TCD param-

eters to existing prediction models (Chapter 3.4).

Prediction

We validated 7 prediction models in our cohort of patients with a recent TA or ischemic stroke.

Our cohort consisted of 598 patients, which may seem rather small to perform external valida-

tion of these prediction models. Nevertheless, the results showed clear distinction between

population based models and models based in patients with a recent TIA or stroke (Chapter

3.1).

We validated two-year risk using survival analysis which was not easy because of the cen-

soring. Censoring occurs when patients are withdrawn from survival analysis after a certain

time point because they have either already reached the outcome event, or when the end of

the follow-up period is reached. In our study some patients only had a few months follow-up

because the end of the study period was reached. Of these patients it is unknown whether they

would experience an outcome event in the near future or not. Thus, they do not contribute the

same amount of information to the analysis as patients with long follow-up. Usually, external

validation concerns diagnostic test, not prognostic tests.

The discrimination was calculated using the c-statistic and the Net Reclassification Index (NRI).

The c-statistic is derived from the sensitivity and specificity of a model, the NRI calculates the

proportion of patients who were reclassified correctly after adding a parameter to the predic-

tion model versus the proportion of patients who were reclassified incorrectly. The c-statistic

was adjusted for censoring, the NRI was not adjusted for censoring. The statistical analysis using

the NRI is new and has not been used in survival analysis before. It would be logical to adjust for

duration of follow-up, or at least stratify for this duration since risk of recurrent events increases

Chap

ter 4

122

with time of exposure. This method has however not yet been developed. This is a methodologi-

cal restriction which cannot be overcome for now. However, in our study, the c-statistic as well

as the NRI showed improvement of the ABCD2 prediction model when both the fifth quintile

of MFV and PI-MFV ratio were added (Chapter 3.4). Moreover, as the comparison of NRI’s was

based on the same dataset, most of the bias because of censoring would be canceled out.

Finally, we used calibration graphs with only 5 groups because of the low number of patients

and therefore outcome events. Fortunately, only few prediction models showed outliers.

cLinicAL imPLicAtions AnD Future reseArch

Diagnostic value of transcranial Doppler ultrasonography

Mean Flow velocity

The finding that MFV is related to several vascular risk factors such as age, male sex,diabetes,

cholesterol, and hypertension is not surprising (Chapter 2.1). These vascular risk factors lead to

arterial stiffness19 and MFV increases with narrowing of the arterial vessels. Thus, MFV can be

regarded as a general measure of systemic disease, atherosclerosis. In this thesis I have focused

on one measurement, but it would be very interesting to investigate whether MFV changes

with aggressive treatment of the vascular risk factors such as diabetes, hypercholesterolemia,

and hypertension, as well as cessation of smoking. Future research could include serial TCD

investigation to answer that question.

Cerebrovascular CO2-reactivity

In my study, cerebrovascular CO2-reactivity was related to cholesterol: the cerebrovascular CO2-

reactivity decreased when total serum cholesterol increased chapter 2.1). This is in accordance

with results of studies in the healthy population.20 In the healthy population CO2-reactivity is

related to white matter lesions,21,22 but this could not be reproduced in our patients with a TIA

or minor stroke. The cerebrovascular CO2-reactivity was not related to the other vascular risk

factors in this study. Silvestrini et al. however, showed that smoking has a short-term, direct

effect on the cerebrovascular CO2-reactivity.23 This provides suggestions for future research: it

would be interesting to investigate the cerebrovascular CO2-reactivity before and after cessa-

tion of smoking.

Micro-embolic signals

The occurrence of MES can clearly discriminate between non-lacunar and lacunar stroke, since

MES are not present in lacunar stroke. These findings apply only to the acute phase of stroke.

The sensitivity of MES is low, which indicates that MES are not a frequent finding in stroke


patients without carotid artery disease. Specificity, on the contrary, is very high which means

that when MES are present, one may safely assume that the stroke was non-lacunar. Usually,

non-lacunar stroke is a clinical diagnosis, but in some patients without a visible infarction on the

first CT-scan of the head cortical symptoms may be mild or transient and therefore overlooked.

The occurrence of MES is higher in the acute phase of stroke24 then in a later phase of stroke.25

For screening of a PCSE, the presence of MES is not discriminatory (Chapter 2.3). Both sen-

sitivity and specificity are not high. This has not been investigated in a cohort of unselected

stroke patients before. In future, very early MES detection in a population of unselected stroke

patients could possibly answer that question.

For MES detection, patients have to wear a metal headband for at least 30 minutes. This is

very inconvenient, especially for older patients in the early phase of stroke. Some newer TCD

systems do not work with these unfriendly headbands, but with recording systems where the

transducer is held in place on a glasses frame.26 With these systems patients can be ambula-

tory and even 24 hr registrations can be possible. Especially in patients with an asymptomatic

carotid artery stenosis longer duration of TCD registration increases the probability of finding

MES.27

Prognostic value of transcranial Doppler ultrasonography

Mean Flow velocity

Mean flow velocity is a prognostic factor for recurrent vascular events after TIA or minor ischemic

stroke (Chapter 3.2). In the general population this is a linear relationship.28 In our study, this

increased risk of recurrent vascular events only occurred in patients in the highest quintile of

MFV. The PI-MFV ratio also showed an increased risk of recurrent vascular events implying that

high peripheral vascular resistance is an important factor in the occurrence of vascular events.

There are strong indications that PI is related to small vessel disease,29 and MFV is related to the

vessel diameter. It is therefore not surprising that the PI-MFV ratio shows an increased risk of

recurrent vascular events. To further evaluate this new factor TC-Duplex would be more helpful

since it can also measure vessel diameter as well as flow velocities in the major cerebral arteries.

These measurements should preferably be performed in the acute phase of stroke.

Cerebral CO2 reactivity

The prognostic value of cerebrovascular CO2-reactivity has not yet been elucidated. In our

study in patients without a carotid artery stenosis, the cerebrovascular CO2-reactivity was not

related to recurrent major vascular events or recurrent stroke (Chapter 3.2). We investigated

patients without a carotid artery stenosis since the presence of MES has already been exten-

sively investigated in patients with a carotid artery stenosis; in these patients, cerebrovascular

CO2-reactivity is a prognostic factor for recurrent stroke, both in symptomatic patients,30-33 and

Chap

ter 4

124

asymptomatic patients.30,34 Molina et al. have found that in the normal population an impaired

cerebrovascular CO2-reactivity was a marker for first-ever lacunar infarction.35 In our study, we

have not made the distinction between lacunar infarction and non-lacunar infarction in our

outcome events. This may be promising to investigate in future.

Micro-Embolic Signals

The occurrence of MES in our population was low, but when MES were present, this was a

strong prognostic factor for recurrent vascular outcome events (Chapter 3.3). We excluded

patients with a carotid artery stenosis who were planned for carotid surgery. These patients

were excluded because carotid artery stenosis is related to the presence of MES,5 and in these

patients risk of recurrent events would be affected by the carotid surgery, as mentioned before.

In patients with a carotid artery stenosis presence of MES is higher, varying from 6% in patients

with an asymptomatic carotid artery stenosis36 to 45% in patients with a symptomatic carotid

artery stenosis.37 It would be interesting to evaluate the presence of MES in patients with mild

carotid artery stenosis (30 to 70%). In these patients, the prognostic value of MES still has to

be determined to evaluate if MES detection is worthwhile in these patients. In our study, we

performed off-line analysis of audio tapes to detect MES. This is time consuming, especially

when prevalence of MES is low. Newer automatic detection show better classification of signals

into MES or artefacts and seem therefore promising.38

Prediction

External validation of several population based models and stroke based models showed that

the ABCD2 prediction model performed best; both calibration and discrimination were fairly

good (Chapter 3.1). Adding MFV and PI-MFV ratio improved this prediction model (Chapter 3.4).

Our study was one of the first to externally validate this model; ours is the only study which has

looked at improvement of this model by adding TCD parameters. Adding the presence of brain

infarction in CT improves the ABCD2 model, which resulted in the ABCD2I model.39 It would be

interesting to evaluate the improvement of the ABCD2 model with both TCD parameters and

the presence of brain infarction on CT for the long-term prediction of recurrent vascular events

after stroke.

Final conclusion

Our results indicate that TCD is a promising technology in patients with a recent TIA or ischemic

stroke, especially MES detection and measurement of flow velocities. MES detection, however,

seems more promising in the early after stroke onset since MES are more often present in the

acute phase. 24 The prognostic value of MES in the acute phase of stroke for the long-term

prediction of recurrent stroke or other vascular events has not been elucidated and should be

studied further.


Most importantly, MFV measured in the middle cerebral artery is an independent prognostic

factor for recurrent vascular events such as ischemic stroke, non-fatal myocardial infarction and

vascular death, as well as the combined PI-MFV ratio. The MFV improves the prediction of recur-

rent vascular events, when added to clinical prognostic variables. This finding addresses one

major question of this thesis. The challenge for the future is to further improve the diagnostic

and prognostic impact of transcranial ultrasound, by using more sophisticated techniques and

at the same time improving patient-friendliness.

Chap

ter 4

126

reFerences

1. Rothwell PM, Giles MF, Flossmann E, Lovelock CE, Redgrave JN, Warlow CP, Mehta Z. A simple score (ABCD) to identify individuals at high early risk of stroke after transient ischaemic attack. Lancet 2005;366:29-36.

2. Holzer K, Feurer R, Sadikovic S, Esposito L, Bockelbrink A, Sander D, Hemmer B, Poppert H. Prognostic value of the ABCD2 score beyond short-term follow-up after transient ischemic attack (TIA)--a cohort study. BMC Neurol 2010;10:50.:50.



5. Molloy J, Markus HS. Asymptomatic embolization predicts stroke and TIA risk in patients with carotid artery stenosis. Stroke 1999;30:1440-3.

6. Visser GH, van Huffelen AC, Wieneke GH, Eikelboom BC. Bilateral increase in CO2 reactivity after unilateral carotid endarterectomy. Stroke 1997;28:899-905.

7. Maltezos CK, Papanas N, Papas TT, Georgiadis GS, Dragoumanis CK, Marakis J, Maltezos E, Lazarides MK. Changes in blood flow of anterior and middle cerebral arteries following carotid endarterectomy: a transcranial Doppler study. Vasc Endovascular Surg 2007;41:389-96.

8. Georgiadis D, Baumgartner RW, Karatschai R, Lindner A, Zerkowski HR. Further evidence of gaseous embolic material in patients with artificial heart valves. J Thorac Cardiovasc Surg 1998;115:808-10.



11. Hong KS, Yegiaian S, Lee M, Lee J, Saver JL. Declining stroke and vascular event recurrence rates in secondary prevention trials over the past 50 years and consequences for current trial design. Circula-tion 2011;123:2111-9.

12. Heart Protection Study Collaborative Group. MRC/BHF Heart Protection Study of cholesterol lower-ing with simvastatin in 20,536 high-risk individuals: a randomised placebo-controlled trial. Lancet 2002;360:7-22.

13. Chapman N, Huxley R, Anderson C, Bousser MG, Chalmers J, Colman S, Davis S, Donnan G, MacMahon S, Neal B, Warlow C, Woodward M. Effects of a perindopril-based blood pressure-lowering regimen on the risk of recurrent stroke according to stroke subtype and medical history: the PROGRESS Trial. Stroke 2004;35:116-21.

14. Halkes PH, van GJ, Kappelle LJ, Koudstaal PJ, Algra A. Aspirin plus dipyridamole versus aspirin alone after cerebral ischaemia of arterial origin (ESPRIT): randomised controlled trial. Lancet 2006;367:1665-73.



16. Baumgartner I, Behrendt P, Rohner P, Baumgartner RW. A validation study on the intraobserver and interobserver reproducibility of renal artery duplex ultrasound. Ultrasound Med Biol 1999;25:225-31.

17. Maeda H, Etani H, Handa N, Tagaya M, Oku N, Kim BH, Naka M, Kinoshita N, Nukada T, Fukunaga R, . A validation study on the reproducibility of transcranial Doppler velocimetry. Ultrasound Med Biol 1990;16:9-14.

18. Baumgartner RW, Mattle HP, Schroth G. Assessment of >/=50% and <50% intracranial stenoses by transcranial color-coded duplex sonography. Stroke 1999;30:87-92.

19. Tuttolomondo A, Di SR, Di RD, Serio A, D’Aguanno G, Pinto A, Licata G. Arterial stiffness indexes in acute ischemic stroke: relationship with stroke subtype. Atherosclerosis 2010;211:187-94.

20. Bakker SL, de Leeuw FE, Koudstaal PJ, Hofman A, Breteler MM. Cerebral CO2 reactivity, cholesterol, and high-density lipoprotein cholesterol in the elderly. Neurology 2000;54:987-9.


22. Marstrand JR, Garde E, Rostrup E, Ring P, Rosenbaum S, Mortensen EL, Larsson HB. Cerebral perfusion and cerebrovascular reactivity are reduced in white matter hyperintensities. Stroke 2002;33:972-6.

23. Silvestrini M, Troisi E, Matteis M, Cupini LM, Bernardi G. Effect of smoking on cerebrovascular reactiv-ity. J Cereb Blood Flow Metab 1996;16:746-9.


25. Poppert H, Sadikovic S, Sander K, Wolf O, Sander D. Embolic signals in unselected stroke patients: prevalence and diagnostic benefit. Stroke 2006;37:2039-43.

26. Mackinnon AD, Aaslid R, Markus HS. Long-term ambulatory monitoring for cerebral emboli using transcranial Doppler ultrasound. Stroke 2004;35:73-8.

27. Mackinnon AD, Aaslid R, Markus HS. Ambulatory transcranial Doppler cerebral embolic signal detec-tion in symptomatic and asymptomatic carotid stenosis. Stroke 2005;36:1726-30.


29. Kidwell CS, el Saden S, Livshits Z, Martin NA, Glenn TC, Saver JL. Transcranial Doppler pulsatility indices as a measure of diffuse small-vessel disease. J Neuroimaging 2001;11:229-35.


31. Matteis M, Vernieri F, Caltagirone C, Troisi E, Rossini PM, Silvestrini M. Patterns of cerebrovascular reactivity in patients with carotid artery occlusion and severe contralateral stenosis. J Neurol Sci 1999;168:47-51.

32. Silvestrini M, Troisi E, Matteis M, Cupini LM, Caltagirone C. Transcranial Doppler assessment of cerebro-vascular reactivity in symptomatic and asymptomatic severe carotid stenosis. Stroke 1996;27:1970-3.

Chap

ter 4

128

33. Webster MW, Makaroun MS, Steed DL, Smith HA, Johnson DW, Yonas H. Compromised cerebral blood flow reactivity is a predictor of stroke in patients with symptomatic carotid artery occlusive disease. J Vasc Surg 1995;21:338-44.

34. Silvestrini M, Vernieri F, Pasqualetti P, Matteis M, Passarelli F, Troisi E, Caltagirone C. Impaired cere-bral vasoreactivity and risk of stroke in patients with asymptomatic carotid artery stenosis. JAMA 2000;283:2122-7.




38. Keunen RW, Hoogenboezem R, Wijnands R, Van den Hengel AC, Ackerstaff RG. Introduction of an embolus detection system based on analysis of the transcranial Doppler audio-signal. J Med Eng Technol 2008;32:296-304.

39. Giles MF, Albers GW, Amarenco P, Arsava MM, Asimos A, Ay H, Calvet D, Coutts S, Cucchiara BL, Dem-chuk AM, Johnston SC, Kelly PJ, Kim AS, Labreuche J, Lavallee PC, Mas JL, Merwick A, Olivot JM, Purroy F, Rosamond WD, Sciolla R, Rothwell PM. Addition of brain infarction to the ABCD2 Score (ABCD2I): a collaborative analysis of unpublished data on 4574 patients. Stroke 2010;41:1907-13.

summary

Summary 133

Stroke is the third leading cause of death in developed countries, after heart disease and

cancer. Most strokes are ischemic and caused by occlusion of a cerebral artery. This leads to

dysfunction and eventually death of brain tissue through lack of oxygen. This may result in

typical symptoms such as unilateral weakness, language disturbances, unilateral sensory

disturbances, hemianopia, ataxia, or impaired speech. In many patients, cerebral ischemia is

only transient and does not result in persistent symptoms and disability. When disability is

persistent, the event is called an ischemic stroke. In the acute phase of tissue dysfunction, at

most 25% of the patients can be treated with thrombolytic agents, but even when patients can

be treated, treatment is not always successful. Secondary prevention is therefore one of the

main objectives of stroke management. Risk of recurrent stroke is approximately 9-16% annu-

ally after ischemic stroke. Intensive secondary prevention by use of antiplatelet medication and

treatment of high blood pressure and high cholesterol has reduced the annual risk of recurrent

events to approximately 4.5%. Well-known risk factors for stroke or other major vascular events

such as myocardial infarction or vascular death are age, male sex, hypertension, diabetes, and

smoking. Unfortunately, it is still difficult to discriminate between patients with a high risk of

recurrent stroke and patients with a low risk of recurrent stroke.

Transcranial Doppler ultrasonography, the main topic of this thesis, offers noninvasive infor-

mation on the large cerebral arteries. Low frequency (2 MHz) ultrasound can pass through

the bone at the level of the temporal window, which is located just above the ear where the

temporal bone is the thinnest. With this technique, mean flow velocity (MFV), peak systolic

flow velocity (PSV), and enddiastolic flow velocity (EDV) in the middle cerebral artery can be

measured. With these parameters, the pulsatility index (PI) can be calculated: PI=(PSV-EDV)/

MFV. The PI is thought to reflect the peripheral resistance in a large artery. Through inhalation

of 5% carbon dioxide cerebral CO2-reactivity can be measured, a functional TCD test which is

thought to reflect elasticity of the smaller cerebral blood vessels. Micro-embolic signals (MES)

can be measured during a continuous TCD registration.

To evaluate the clinical value of these TCD tests, we have conducted the Rotterdam TCD study.

In this study we have performed TCD registration in 598 consecutive patients with a recent TIA

or minor ischemic stroke. We measured flow velocities, cerebral CO2-reactivity, and presence of

MES during a 30 minute registration. The research questions were:


embolism and the presence of small vessel disease in patients with a TIA or minor ischemic

stroke?


minor ischemic stroke by means of TCD investigation?

Sum

mar

y

134

To answer these questions we have firstly evaluated the diagnostic value of TCD in chapter

2. chapter 2.1 describes the relationship between TCD parameters and vascular risk factors.

Blood flow velocity in the MCA decreases with age, and is lower in men than in women. Blood

flow velocity in the MCA increases with total serum cholesterol, and is increased in diabetics

compared to non-diabetics. Cerebrovascular CO2-reactivity is lower in hypertensive patients

and decreases with increasing total serum cholesterol. Our results indicate that the cerebral

flow velocity in the MCA is influenced by multiple interacting factors.

In chapter 2.2 we show the relationship between skull thickness, bone density, and window

failure. Window failure (WF) means that no adequate TCD signal can be obtained. Window

failure is more common in older women. We conclude that both thickness and density of the

temporal bone are related to the presence of WF, but that skull density does not independently

predict WF. Absence of WF can be predicted accurately in nearly all patients with ischemic

stroke or TIA by means of three simple parameters: skull thickness, age and gender.

In chapter 2.3 we review studies on the diagnostic value of TCD in patients with a TIA or minor

ischemic stroke. We give an overview of studies which evaluated whether the presence of MES

can distinguish between patients with a lacunar infarction (small vessel disease) and patients

with a cortical infarction (non-small vessel disease). We also give an overview of studies which

evaluated whether TCD can be helpful in detection of a potential cardiac source of embolism

(PCSE). We have combined these results with our own findings. Our results indicate that TCD

could be a useful test to distinguish non-small vessel disease from small vessel disease. For a

PCSE, TCD alone does not seem able to adequately distinguish between the presence and the

absence of a PCSE.

In chapter 3 we describe the prognostic value of TCD. In chapter 3.1 we validate predictions

from seven well-known prediction models in our own cohort of patients. Prediction models

derived from stroke cohorts perform better than population-based prediction models in

prediction of 2-year risk of recurrent vascular events. Of these prediction models, the ABCD2

prediction model seems to be most adequate and most easily applicable in clinical practice.

In chapter 3.2 we investigate the prognostic value of the individual TCD parameters. Because

of the expected interaction between MFV and PI, we created a new parameter, the PI-MFV ratio

that MFV and PI-MFV ratio, calculated as PI/MFV*100. MFV and PI-MFV ratio, measured in the

MCA by TCD, are independent risk factors for recurrent stroke. Interestingly, MFV and PI-MFV

ratio were also associated with the occurrence of major vascular events (combined outcome

measure “stroke, MI, and vascular death”). This suggests that the MFV and PI-MFV ratio reflect

not only the condition of the major cerebral blood vessels, but also that of coronary and periph-

eral arteries.

Summary 135

chapter 3.3 shows that MES are not often present in patients with a recent TIA or ischemic

stroke without a carotid artery stenosis, only in 4%. However, MES do indicate increased risk for

recurrent stroke in these patients.

In chapter 3.4 we show that adding MFV and MES to the ABCD2 prediction model improves

calibration as well as discrimination of this model. Calibration measures how closely predicted

outcomes agree with actual outcomes. Discrimination refers to the ability to distinguish

between patients who will have an outcome event and those who will not. This chapter shows

that MES and a MFV>60.5 cm/s in the MCA are independent prognostic factors for long term

prognosis in patients with a recent TIA or minor ischemic stroke when added to the ABCD2 pre-

diction model. Moreover, adding these two factors to the ABCD2 prediction model improves

calibration as well as discrimination.

In chapter 4 I reflect on the main findings in the context of current knowledge and give sug-

gestions for future research.

On the basis of our studies and current literature we conclude that TCD could be a useful

test to distinguish non-small vessel disease from small vessel disease, but not for the detection

of a PCSE. TCD parameters such as MFV and cerebral CO2-reactivity are related to vascular risk

factors such as age, gender, diabetes, cholesterol, and hypertension. This implies that in future

studies of TCD parameters as prognostic or diagnostic factors in patients with a TIA or stroke,

ultrasound findings will have to be adjusted for these vascular risk factors.

The presence of MES is a prognostic factor in patients with a recent TIA or ischemic stroke,

even in patients without a carotid artery stenosis. Detection of MES is, however, time-consum-

ing; occurrence of MES is low in patients without a carotid artery stenosis. MFV and PI-MFV ratio

seem to reflect atherosclerosis. These parameters are prognostic factors after a TIA or minor

ischemic stroke. Adding MES and MFV to the ABCD2 prediction model improves the calibration

and discrimination of this model. These findings will have to be further investigated in larger

studies.

samenvatting

Samenvatting 139

Een beroerte is de derde doodsoorzaak in Westerse landen na hartziekten en kanker. Het

merendeel van de beroertes wordt gevormd door herseninfarcten. Hierbij wordt een bloedvat

in de hersenen afgesloten. Dit leidt tot zuurstofgebrek en sterfte van hersencellen waardoor er

functiestoornissen van de hersenen ontstaan. Deze functiestoornissen uiten zich onder andere

als éénzijdig krachtsverlies, spraakstoornissen, coördinatiestoornissen, gezichtsvelduitval of

een taalstoornis. Soms verdwijnen de verschijnselen weer en spreekt men achteraf van een

tijdelijke ischemische aanval oftewel transient ischemic attack: een TIA. Als er blijvende schade

optreedt gaat het om een herseninfarct. In de acute fase kan momenteel hooguit 25% van de

patiënten behandeld worden met aggressieve bloedverdunners (trombolytica), en deze behan-

deling is ook niet altijd succesvol. Om die reden is preventie van toekomstige herseninfarcten

of andere uitingen van hart- en vaatziekten bij patiënten met TIA’s of herseninfarcten uitermate

belangrijk. Het risico op nieuwe beroertes of andere uitingen van hart- en vaatziektes bij deze

patiënten is ongeveer 9 tot 16% per jaar. Dit risico wordt teruggebracht tot ongeveer 4.5%

na starten van intensieve medicameneuze preventie zoals bloedplaatjes-aggregatieremmers,

antihypertensiva en statines. De belangrijke risicofactoren zijn hoge leeftijd, mannelijk

geslacht, hoge bloeddruk, roken en diabetes mellitus. Helaas is het nog steeds niet mogelijk

om te voorspellen wie wel of wie juist opnieuw een herseninfarct of andere uiting van hart- en

vaatziekten zal krijgen.

Met transcranieel Doppler ultrageluid (TCD) kan men non-invasief informatie krijgen over de

grote bloedvaten in de hersenen. Net boven het oor is het “temporale bot window” oftewel

“temporal bone window” gelokaliseerd. Hier is het bot iets dunner waardoor ultrageluid (2

MHz) door het bot heen dringt. Hiermee kan in de arteria cerebri media de gemiddelde snel-

heid (MFV), de pieksystolische snelheid (PSV) en de einddiastolische snelheid (EDV) van het

bloed worden gemeten. Aan de hand van deze waarden kan de pulsatility index (PI) worden

berekend: PI=(PSV-EDV)/MFV. Dit is een maat voor de perifere weerstand in een slagader.

Met toediening van kooldioxide kan de cerebrale CO2-reacitiviteit worden gemeten, een test

waarmee de elasticiteit van de kleine bloedvaten in de hersenen wordt gemeten. Als derde

kan tijdens een langdurige registratie het aantal micro-embolische signalen (MES) worden

gemeten. Dit zijn luidere signalen die suggereren dat er een partikel in de bloedbaan passeert,

dit kan onder andere een luchtbelletje, of een stolsel zijn.

Om meer inzicht te krijgen in de klinische waarde van deze tests hebben we de Rotterdam

TCD Studie uitgevoerd. Hierbij hebben we bij 598 opeenvolgende patiënten met een TIA of

een licht herseninfarct TCD metingen gedaan waarbij, indien mogelijk, de snelheden in de

arteria cerebri media en de cerebrale CO2-reactiviteit gemeten, en de aanwezigheid van MES

geregistreerd gedurende een half uur. In deze studie stonden twee vraagstellingen centraal:

1. Heeft TCD diagnostische waarde in het detecteren van een cardiale emboliebron en het

detecteren van subtype van ee herseninfarct bij patiënten met een TIA of licht herseninfarct?

Sam

enva

ttin

g

140

2. Is het mogelijk om patiënten met een hoog risico op nieuwe vasculaire events (gebeurte-

nissen) na een TIA of licht herseninfarct te identificeren met TCD? Zo ja, kan TCD huidige

predictiemodellen verbeteren?

Om deze vragen te kunnen beantwoorden hebben we in hoofdstuk 2 allereerst gekeken naar

de diagnostisch waarde van TCD. hoofdstuk 2.1 beschrijft allereerst welke risicofactoren van

invloed zijn op de TCD metingen. Gebleken is dat oudere leeftijd en het mannelijk geslacht

gerelateerd zijn aan lagere snelheden in de arteria cerebri media. De aanwezigheid van diabe-

tes en de aanwezigheid van hypercholesterolemie waren juist gerelateerd aan hogere snelhe-

den in de arteria cerebri media. De cerebrale CO2-reactiviteit is gemiddeld lager bij patiënten

met hypertensie of hypercholesterolemie. Dit betekent dat de TCD parameters door multipele

factoren beinvloed worden en dat hier voor gecorrigeerd moet worden bij analyses naar de

diagnostische of prognostische waarde van deze TCD parameters.

In hoofdstuk 2.2 laten we de relatie zien tussen schedeldikte, densiteit van het schedelbot en

de kans op window failure. Window failure betekent dat er geen goed TCD signaal verkregen

kan worden. Dit treedt vaker op bij met name oudere vrouwen. In dit hoofdstuk tonen we aan

dat zowel de schedeldikte als densiteit ook gerelateerd zijn aan het optreden van window

failure. Wij hebben ook een predictiemodel ontwikkeld met als variabelen leeftijd, geslacht,

schedeldikte en schedeldensiteit, waarmee vrij accuraat kan worden voorspeld of er sprake zal

zijn van window failure of niet.

In hoofdstuk 2.3 wordt gekeken naar de diagnostische waarde van TCD bij patiënten met een

TIA of een licht herseninfarct. Wij geven allereerst een overzicht van studies die onderzoek heb-

ben gedaan of de aanwezigheid van MES kan differentiëren tussen patiënten met een lacunair

of corticaal herseninfarct. Hierna hebben we ook onderzocht of de aanwezigheid van MES een

cardiale emboliebron kan detecteren. Deze bevindingen hebben we gecombineerd met onze

eigen resultaten. Onze resultaten laten zien dat TCD nuttig kan zijn om onderscheid te maken

tussen een corticaal en een lacunair infarct. TCD heeft echter geen diagnostische waarde in het

detecteren van een cardiale emboliebron.

In hoofdstuk 3 beschrijven we in op de prognostische waarde van TCD. Allereerst hebben we

in hoofdstuk 3.1 zeven gerenommeerde predictiemodellen met elkaar vergeleken door ze te

valideren op onze eigen dataset. Hierbij kwam naar voren dat predictiemodellen die afgeleid

zijn van grote groepen patiënten met een eerdere TIA of herseninfarct beter het 2-jaars risico

op nieuwe vasculaire events voorspellen dan predictiemodellen die op de algemene populatie

gebaseerd zijn. Van deze predictiemodellen is het ABCD2 predictiemodel vrij betrouwbaar en

makkelijk te hanteren aangezien er weinig variabelen gebruikt worden in dit predictiemodel.

Samenvatting 141

hoofdstuk 3.2 toont aan dat een hoge snelheid in de arteria cerebri media (meer dan 60.5 cm/

seconde) een verhoogde kans geeft op zowel nieuwe beroertes als nieuwe vasculaire events.

Omdat er ook een interactie werd verwacht tussen de PI en de MFV hebben we een nieuwe

factor gecreëerd: de PI-MFV ratio (berekend als PI/MFV*100). Deze interactiefactor heeft een

lineaire relatie met het risico op nieuwe beroertes en nieuwe vasculaire events. MFV en de

PI-MFV ratio zijn prognostische factoren na een TIA of een licht herseninfarct, onafhankelijk

van andere risicofactoren. Mogelijk reflecteren deze parameters niet alleen de mate van athe-

rosclerose in de hersenslagaders, maar ook in de rest van het cardiovasculaire systeem.

In hoofdstuk 3.3 hebben we de prognostische waarde van MES onderzocht bij patiënten

zonder een carotisstenose. Deze MES komen slechts bij 4% van de patiënten met een TIA of

licht herseninfarct zonder carotisstenose in onze studie voor. Bij aanwezigheid van deze MES is

er echter een verhoogd risico op nieuwe beroertes.

In hoofdstuk 3.4 onderzoeken we of toevoeging van TCD parameters aan het ABCD2 predic-

tiemodel voorspelling van nieuwe vasculaire events verbetert. Hierbij hebben we gekeken

naar de calibratie en de discriminatie. De calibratie meet hoe goed voorspelde vasculaire

events overeenkomen met daadwerkelijk opgetreden vasculaire events. Discriminatie verwijst

naar het vermogen om onderscheid te kunnen maken tussen patiënten met een hoog risico

op nieuwe vasculaire events en patiënten met een laag risico op nieuwe events. Toevoeging

van de aanwezigheid van MES en MFV > 60.5 cm/seconde verbetert zowel de calibratie als de

discriminatie van het ABCD2 predictiemodel.

In hoofdstuk 4 worden de belangrijkste bevindingen in de context van de bestaande literatuur

besproken en worden suggesties voor verder onderzoek gedaan.

Op basis van onze studies en de literatuur concluderen wij dat TCD geen waarde heeft bij

het onderscheid maken tussen een corticaal of een lacunair infarct. Ook helpt TCD niet bij het

detecteren van een cardiale emboliebron. Wel zien wij een duidelijke relatie tussen cardio-

vasculaire risicofactoren en TCD parameters zoals de MFV en de cerebrale CO2-reactiviteit. Dit

betekent dat bij onderzoeken naar deze parameters altijd voor cardiovasculaire risicofactoren

gecorrigeerd moet worden.

De aanwezigheid van MES is prognostisch van belang, ook voor patiënten zonder carotisste-

nose. Het detecteren van MES is echter nog tijdrovend en MES komen weinig voor bij patiënten

zonder carotisstenose. De MFV en de PI-MFV lijken een mate van atherosclerose te weerspie-

gelen; deze parameters hebben naast de eenvoudige klinische parameters een duidelijke

prognostische waarde na een TIA of licht herseninfarct. Wanneer MFV and MES toegevoegd

worden aan het ABCD2 predictiemodel verbeteren zowel de calibratie als de discriminatie

van dit model. Deze bevindingen zullen echter in een groter onderzoek gerepliceerd moeten

worden.

List of abbreviations

List of abbreviations 145

TIA Transient ischemic attack

MES Micro-embolic signals

TCD Transcranial Doppler ultrasonography

MFV Mean flow velocity

PSV Peak systolic flow velocity

EDV Enddiastolic flow velocity

PI Pulsatility index

PCSE Potential cardiac source of embolism

MCA Middle cerebral artery

CT Computed tomography

ROI Region of interest

WF Window failure

AF Atrial fibrillation

PI/MFV ratio 100xPI/MFV

NRI Net reclassification index

List of publications

List of publications 149

Wijnhoud AD, Lingsma HF, Steyerberg EW, Koudstaal PJ, Dippel DWJ. Improving prediction

of major vascular events in patients with a TIA or ischemic stroke with transcranial Doppler

ultrasonography. Submitted to Stroke

Wijnhoud AD, Koudstaal PJ, Dippel DWJ. Micro-embolic signals and risk of vascular events in

patients with a TIA or ischemic stroke and without severe carotid disease. Submitted to J Clin

Ultrasound

Wijnhoud AD, Koudstaal PJ, Dippel DWJ. The prognostic value of pulsatility index, flow velocity,

and their ratio, measured with TCD ultrasound, in patients with a recent TIA or ischemic stroke.

Acta Neurologica Scandinavia. 2011:238-44

Wijnhoud AD, Maasland E, Lingsma HF, Steyerberg EW, Koudstaal PJ, Dippel DWJ. Prediction

of major vascular events in patients with a recent TIA or ischemic stroke. A comparison of 7

models. Stroke. 2010:2178-85

Wijnhoud AD, Franckena M, van der Lugt A, Koudstaal PJ, Dippel DWJ. Skull thickness and bone

density as predictors of an inadequate acoustical temporal bone window in transcranial Dop-

pler ultrasound. Ultrasound Med Biol. 2008: 923-9.

Wijnhoud AD, Koudstaal PJ, Dippel DWJ. Relationships of transcranial blood flow Doppler

parameters with major vascular risk factors: TCD study in patients with a recent TIA or non-

disabling ischemic stroke. J Clin Ultrasound. 2006:70-6.

Bakker SL, Boon AJ, Wijnhoud AD, Dippel DWJ, Delwel EJ, Koudstaal PJ. Cerebral hemodynamics

before and after shunting in normal pressure hydrocephalus. Acta Neurol Scand. 2002:123-7.

Janssen HLA, Wijnhoud A, Haagsma EB, van Uum SHM, van Nieuwkerk CMJ, Adang RP, Chamu-

leau RAFM, van Hattum J, Vleggaar FP, Hansen BE, Rosendaal FR, van Hoek B. Extrahepatic portal

vein thrombosis: aetiology and determinants of survival. Gut. 2001:720-4.

Saxena R, Wijnhoud AD, Koudstaal PJ, Meiracker AH. Induced elevation of blood pressure in the

acute phase of ischemic stroke in humans. Stroke. 2000:546-8.

Saxena R, Wijnhoud AD, Carton H, Hacke W, Kaste M, Przybelski RJ, Stern KN, Koudstaal PJ. A

controlled safety study of a hemoglobin therapeutic, DCLHb, in acute ischemic stroke. Stroke.

1999:993-6.

Saxena R, Wijnhoud AD, Man in’t Veld AJ, Meiracker AH, Boomsma F, Przybelski RJ, Koudstaal

PJ. Diaspirin Cross-linked Hemoglobin. Effect on Endothelin-1 and Blood Pressure in Acute

Ischemic Stroke in Man. Journal of Hypertension 1998:1459-65.

About the author

About the author 153

Annemarie Dagmar Wijnhoud was born on the 7th of August 1972 in Zwolle, The Netherlands.

She attended secondary school at the “Gymnasium Haganum” in The Hague. She graduated in

1990. She started her training in Medicine in 1991 at the Erasmus University of Rotterdam. From

1995 to 1996 she worked as student assistant under the supervision of Dr. R. Saxena and Prof.

Dr. P.J. Koudstaal on the DIAS trial, a controlled safety study of a hemoglobin DCLHb (Diaspirin

Cross-linked Hemoglobin) in acute ischemic stroke. She graduated in April 1999 from medical

school. In that month she started working on the Rotterdam TCD Study, the study underlying

this thesis. In February 2003 she started her training as a neurologist at the department of

Neurology at the Erasmus Medical Centre Rotterdam (Prof. Dr. P.A.E. Sillevis Smitt). Since 2010

she has been working as a neurologist in the IJsselland ziekenhuis in Capelle aan den IJssel.

Dankwoord

Dankwoord 157

Na een lange periode is nu het moment gekomen om als laatste onderdeel van dit proefschrift

het dankwoord te mogen schrijven. Ik wil graag iedereen bedanken die geholpen heeft bij de

tot standkoming van dit proefschrift op welke wijze dan ook. Graag noem ik een aantal met

name.

Als eerste prof. dr. D.W.J. Dippel. Beste Diederik, ik heb zo veel van je geleerd, met name hoe

je alles zelf moet kunnen! Gek werd ik van de stata problemen waarbij jij maar bleef beweren

dat het kon. Uiteindelijk kreeg ik ook wel eens gelijk. Jouw onaflatend positivisme nadat onze

eerste review volledig de grond in werd geboord door meerdere reviewers kan ik alleen maar

waarderen. Ik kan me niet meer herinneren hoe vaak jij wel niet de beroemde woorden hebt uit-

gesproken: “Mijn eerste artikel werd pas door het 7e tijdschrift geaccepteerd en kreeg lovende

kritieken”. Uiteindelijk werd ons hoofdartikel ook pas bij het 7e tijdschrift geaccepteerd, een

lovend voorwood was echter nergens te bekennen. Mijn hartelijke dank dat je mijn leermeester

bent geweest en bovenal dank voor jouw geduld met mij.

En natuurlijk de tweede promotor prof. dr. P.J. Koudstaal. Beste Peter, enorm bedankt voor de

geboden kans. Het is eigenlijk allemaal begonnen toen wij samen in een kwaliteitscommissie

voor het onderwijs zaten; ik als student, jij als voorzitter. Hierna ben ik als student onderzoek

gaan doen bij jou en van het één kwam het ander en nu is dit proefschrift eindelijk afgerond.

Het meest contact liep via Diederik, maar als ik dan met jou een afspraak had was het altijd weer

leuk en gezellig als vanouds. Nogmaals hartelijk dank voor de geboden kans.

De overige leden van de beoordelingscommissie, prof. dr. A. van der Lugt, prof. dr. E.W. Stey-

erberg en prof. dr. J. Stam wil ik graag bedanken voor het beoordelen van dit proefschrift. Prof

dr. W. Mess, prof. dr. E. Boersma en dr. F.E. de Leeuw wil ik bedanken voor het zitting nemen in

de commissie.

Alle co-auteurs wil ik danken voor zijn of haar bijdrage bij het aanscherpen van de manuscrip-

ten waardoor uiteindelijk mooie artikelen gepubliceerd konden worden.

Uiteraard wil ik Hanneke Hilkemeijer, Naziha El Ghanouti en Esther van der Heijden bedanken

voor het bellen van patiënten en het invoeren van alle data. Zonder jullie fanatieke gebel had-

den we de follow-up data niet zo uitgebreid gehad. Enorm bedankt!

De mede-onderzoekers met wie ik tegelijkertijd op de 22e verdieping heb gebivakkeerd wil ik

graag bedanken voor de gezelligheid: Beste Sonia, Rinske, en de rest: het was leuk! Mary-Lou

en Lisette: leuk dat we nog steeds bekend staan als Diederik’s Angels. Dank voor de geestelijke

steun.

Dan

kwoo

rd

158

Alle medeonderzoekers van de neurovasculaire groep wil ik bedanken voor de morele steun en

de gezelligheid. Heleen, bedankt voor je stimulerende adviezen en positivisme. Maaike, jij bent

uiteindelijk eerder gepromoveerd, bedankt voor de leuke tijd.

Prof. Dr. P.S. Sillevis Smitt, beste Peter, bedankt voor de leuke opleidingstijd! Ik waardeer jouw

vertrouwen in mij enorm.

Marcel, Huib en Pieter, bedankt voor het enthousiasme in het mee bedenken van de stellingen.

Jammer genoeg zijn de door ons in Stockholm bedachte stellingen allemaal afgekeurd.

Lieve Matthé, bedankt voor je hulp! Ik wist niet dat jij zo’n goede editor was! Dank voor je

welwillendheid en je nuttige tips.

Uiteraard wil ik mijn paranimfen bedanken voor alle hulp de afgelopen maanden. Heerlijk dat ik

met jullie allebei een heel goede klik heb gehad tijdens de opleiding. Beste Sarah en Janet, wat

mij vooral bij zal blijven is het enthousiasme waarmee jullie mijn paranimf wilden zijn! Ik voel

me vereerd! Ik ben erg blij geweest met alle praktische tips en opjutmomenten van de laatste

tijd. Bedankt voor jullie vriendschap.

Uiteindelijk zijn het de patiënten geweest die ervoor hebben gezorgd dat dit proefschrift tot

stand kon komen. Hartelijk dank voor de deelname aan mijn onderzoek.

Lieve Stef, Thomas en Lucas: bedankt dat julie er voor mij zijn en het leven mooier maken.

The clinical value of transcranial doppler ultrasonography in patients ...

Documents

Transcript of The clinical value of transcranial doppler ultrasonography in patients ...